IOS 2024: INFORMS OPTIMIZATION SOCIETY CONFERENCE 2024

This page contains an index consisting of author-provided keywords.

A
Academic rankings	The minimum feedback arc set problem over bidirectional graphs with an application to faculty hiring networks
accelerated algorithms	High probability and risk-averse guarantees for stochastic saddle point problems
accelerated gradient descent	A simple uniformly optimal method without line search for convex optimization
acceleration	Toward a grand unified theory of accelerations in optimization and machine learning
Access control	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
actor-critic	Neural Network Approaches for Parameterized Optimal Control
Adaptive	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions.
Adaptive Algorithms	Advancing SGD: Exploring the Interplay of Stochastic Polyak Step-size and Momentum
adaptive experimentation	Adaptive Experimentation at Scale
adaptive methods	Stochastic FISTA with fully adapative step sizes.
adaptive optimization	Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
Adaptive Partitioning	Adaptive Partitioning for Chance-Constrained Problems with Finite Support
Adaptive robust optimization	An exact method for a class of robust nonlinear optimization problems
adaptive sampling	Enabling Scale-up through Multi-fidelity Adaptive Computing Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Decomposition and adaptive sampling for data-driven inverse linear optimization
adaptive step size	Adaptive Federated Learning with Auto-Tuned Clients
Adaptivity	Adaptive Bin Packing with Overflow
Adaptivity Gap	Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
Adaptivity gaps	Adaptivity Gaps in Two-sided Assortment Optimization
Adjustable risk	Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks
adjustable robust optimization	Decision-making with Side Information: A Causal Transport Robust Approach
ADMM	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions. New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
Advanced Available-to-Promise (AATP)	Solving an Advanced Available-to-Promise (AATP) Problem by Optimization and Meta-heuristics Techniques
adversarial Markov Decision Processes	No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions
Adversarial Robust	On the Adversarial Robustness of Benjamini Hochberg
Adversarial robust learning	Regularization for Adversarial Robust Learning
Adversarial robustness	PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification Adversarial Robustness in the Streaming Model
affine hull	Computing implicit equalities of a linear inequality system
affine policy
Agent Agnostic Mechanisms	Follower Agnostic Methods for Stackelberg Games
Aggregated limited-memory	Aggregated Limited-Memory Rank-1 Cuts
AI for Optimization	Towards Constituting Mathematical Structures for Learning to Optimize
airline	Improved Airline Network Topologies for Building Resilient & Robust Aviation Infrastructures
Algorithm Stability	Generalization Performances in Nonconvex Minimax Optimization: A Comprehensive Study
Algorithm Unrolling	Towards Constituting Mathematical Structures for Learning to Optimize
Algorithmic Fairness	f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Algorithmic game theory	Hicksian Unit-Demand Pricing
Algorithmic pricing	Hicksian Unit-Demand Pricing
Algorithms	Recent advances in computing Nash equilibria in Markov Games Algorithms for DC Programming via Polyhedral Approximations of Convex Functions
algorithms with predictions	Branch-and-Bound with Predictions for Variable Selection
almost-sure convergence	Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization
Alternating Current Optimal Power Flow Problem
alternating direction method of multipliers (ADMM)	Computing a directional stationary solution of DC programs via ADMM
alternating sampling framework	Proximal Oracles for Optimization and Sampling
always-active constraints	Computing implicit equalities of a linear inequality system
AMPL	AMPLS Solver Libraries
Analog Computing	Accelerating Continuous Variable Coherent Ising Machines via Momentum
Analysis of algorithms: Data structures	Minimum Cost Adaptive Submodular Cover
Analysis of algorithms: Suboptimal algorithms	Minimum Cost Adaptive Submodular Cover
Ant colony optimization (ACO)	Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network
API	AMPLS Solver Libraries
application	Deep Learning with Nontrivial Constraints
applied category theory	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
approximate linear programming	Self-Adapting Network Relaxations for Weakly Coupled Markov Decision Processes
Approximate Subgradient	Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Convex and Non-Convex Problems
approximation algorithm	Relaxation \& Approximation Algorithm for Solving Sparse PCA Under Robust Uncertainty Set Local Search for Constrained Determinant Maximization
Approximation algorithms	Rigorously Approximating the Local Hamiltonian Problem Min-max-min Optimization with Smooth and Strongly Convex Objectives Hicksian Unit-Demand Pricing An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams Adaptivity Gaps in Two-sided Assortment Optimization Integer programming formulations for partitioning a graph into low-diameter clusters Simple Randomized Rounding for Max-Min Eigenvalue Augmentation When Simple is (Near)-Optimal in Security Games for Urban Transportation Stochastic Scheduling: Strategies for Abandonment Management
Approximation Schemes	Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
Assortment Optimization	Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps Adaptivity Gaps in Two-sided Assortment Optimization
asymptotic bias	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Asymptotic Normality	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Auction Algorithms
Augmented Lagrangian	Stochastic Lagrangian-based method for nonconvex optimization with nonlinear constraints A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach: Part II A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach
augmented Lagrangian methods	Algorithm NCL for constrained optimization: Overcoming LICQ
Autoencoder	Improving Autoencoder Image Interpolation via Dynamic Optimal Transport
Automated scientific discovery	AI Hilbert: A New Paradigm for Scientific Discovery by Unifying Data and Background Knowledge
automatic differentiation	Accelerated Nonlinear Programming on GPUs: Implementing Solver and Automatic Differentiation
autonomous experimentation	Machine learning enhanced meta-heuristic optimization algorithms for autonomous experimentation
autonomy	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
Autoregressive Stochastic Process	A Data-Driven Multistage Stochastic-Robust Optimization Approach with Temporally Correlated Uncertainty
B
b-hull	Determining Sharp Proximity Bounds For Low Row Rank and $\Delta$-Modularity
b-matching
backtracking	A Stochastic GDA Method with Backtracking for Solving Nonconvex (Strongly) Concave Minimax Problems
Balls and Bins	Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
BAM	Branch-and-Model: A Derivative-free Global Optimization Algorithm
bandit	Stochastic Gradient Succeeds for Bandits
Bandits
barrier functions
Basic Algorithm
BASS model	Explicit solutions of the SI and Bass models on random networks
Bayesian Additive Regression Trees	Towards Non-stationary Bayesian Nonparametrics
Bayesian inference	Dynamic Parameter Estimation in Deterministic Dynamical Systems
Bayesian optimization	Robust Personalized Design via Bayesian Optimization under Covariate Uncertainty Bayesian optimization of risk based on Student-t process and extreme value statistics Adaptive Experimentation at Scale Towards Non-stationary Bayesian Nonparametrics Districting with Overlapping Service Regions
Bellman equation	On the Foundation of Distributionally Robust Reinforcement Learning
benchmarking	Benchmarking the Operation of Quantum Heuristics and Ising Machines: Scoring Parameter Setting Strategies on Optimization Applications Performance Benchmarks of Quantum Annealing Hardware
Bender's Decomposition	Adaptive Optimization and Safe Reinforcement for Heparin Doseing
Benders decomposition	Designing Resilient Relay Logistics Networks Using k Shortest Paths
Benjamini Hochberg	On the Adversarial Robustness of Benjamini Hochberg
Best Arm Identification	Maximizing and Satisficing in Multi-armed Bandits with Graph Information
bi-level optimization	Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions
Biclique Covers	Building Formulations for Combinatorial Disjunctive Constraints via Biclique Covers
Bidirectional Search
Big data	Quantify Childbirth Care Inequity for Socioeconomically Disadvantaged Groups
Bilevel Optimization	On Penalty Methods for Bilevel Optimization A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing First-order Methods for Bilevel Optimization Contextual Stochastic Bilevel Optimization Value Function Projections for Discrete Bilevel Optimization A Bilevel Mixed-Integer Program for the Define-Combine Redistricting Procedure SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning An Inexact Conditional Gradient Method for Constrained Bilevel Optimization A Single-Level Reformulation of Integer Bilevel Programs using Decision Diagrams Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems
Bilinear Assignment Problem	An interesting generalization of the Koopman-Beckmans quadratic assignment problem
Bilinear optimization	Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints
bilinear program	Solution of disjoint bilinear programs using simplicial branch-and-bound
Bin Packing	Adaptive Bin Packing with Overflow
Binary Quadratic Problems	Coordinate Partitioning for Difficult Euclidean Max-Sum Diversity Problems
bisubmodular polyhedra	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Black-box optimization	Branching Adaptive Surrogate Search Method for High-dimensional Optimization
Blackbox Optimization	Blind Source Separation with Spatiotemporal Beamforming
Blind Source Separation	Blind Source Separation with Spatiotemporal Beamforming
Block-coordinate Methods	ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization
Blockchain	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
Boosted DCA
Boosted Difference of Convex Functions Algorithm	Boosted Difference of Convex Algorithms for Clustering with Constraints
Boscia	Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe
Bound propagation	Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification
branch and bound	Cone product reformulation for global optimization
branch and price	Branch-and-price for prescriptive contagion analytics
branch-and-bound	Who Plays First? Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms Compressing Branch-and-Bound Trees Branch-and-Bound with Predictions for Variable Selection Branch-and-bound for D-Optimality with fast local search and variable-bound tightening Solution of disjoint bilinear programs using simplicial branch-and-bound Non-Monotonicity of Branching Rules with respect to Linear Relaxations
Branch-and-cut solvers	Efficient relax-and-cut separation in a branch-and-cut solver
Branch-and-Price	Designing Resilient Relay Logistics Networks Using k Shortest Paths
Branching Method	Branching in the Dual Decomposition Method for Stochastic Integer Programs
branching on general disjunctions	Compressing Branch-and-Bound Trees
Bregman primal--dual hybrid gradient method (PDHG)	A globally convergent difference-of-convex algorithmic framework and application to log-determinant optimization problems
Brunn-Minkowski theory	Optimal Regularization for a Data Source
budget constraint	Strategy Investments in Matrix Games
budgeted uncertainty	Recycling Valid Inequalities for Robust Optimization
Burer-Monteiro decomposition	Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
Burer-Monteiro method	Certification of sums of squares via low-rank optimization
Bures–Wasserstein Space	Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
C
C#	AMPLS Solver Libraries
C++	AMPLS Solver Libraries
calibration	Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents Learning Discrete-Time Markov Chains from Aggregate Data
Callbacks	AMPLS Solver Libraries
Capacity expansion	Scalable Climate-Aware Power Grid Capacity Expansion using MPI-SPPY
causal inference	Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment Policy learning without overlap: Pessimism and generalized Bernstein's inequality Applications of 0-1 Neural Networks in Prescription and Prediction
Causal Transport	Adversarially Robust Optimal Control with Causal Transport Distance
Central path	O-minimal structures and central paths in nonlinear optimization
Chambolle-Pock	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
Chambolle-Pock method	Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
Chance constrained optimization	Optimization under Rare Chance Constraints
Chance Constraint	The Terminator: An Integration of Inner and Outer Approximations for Solving Regular and Distributionally Robust Chance Constrained Programs via Variable Fixing Chance-Constrained Fractional Programming under Ambiguity -- Distributionally Robust Maximization of Ratio Exceedance Probability
chance constraints	Mixed-Integer Programming Formulations for Chance-Constrained Optimization with Mixture Models Self-Structured Importance Sampling for Chance-Constrained Optimization Adaptive Partitioning for Chance-Constrained Problems with Finite Support
Chance-Constrained Optimization	Impact of Uncertainty on Fairness
Chance-Constrained Problem	Chance-Constrained Set k-Covering Problem
Chance-constrained programming	Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks
Chvátal-Gomory rank-1 cuts	Aggregated Limited-Memory Rank-1 Cuts
Circuit Cutting	Divide and conquer approach for distributed quantum computing
Classification Theory	Classifying with Uncertain DEA
cloud computing	Model Deployment with GAMS Engine
cloud supply chain	Online Rack Placement in Large-scale Data Centers
Clustering	Boosted Difference of Convex Algorithms for Clustering with Constraints Fair Minimum Representation Clustering
co-design	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
Co-occurrence graph
Coefficient of Prescriptiveness	Robust Data-driven Prescriptiveness Optimization
column generation	DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods Convex Hull Pricing in Electricity Markets: Evidence from a Large US Market Submodular Dispatching with Multiple Vehicles Electric Vehicle Routing: Subpath-Based Decomposition Branch-and-price for prescriptive contagion analytics
Column W property M matrix	Generalizations of R0 and SSM properties for Extended Horizontal Linear Complementarity Problem
Combinatorial Disjunctive Constraints	Building Formulations for Combinatorial Disjunctive Constraints via Biclique Covers
combinatorial optimization	An interesting generalization of the Koopman-Beckmans quadratic assignment problem Hexaly, a new kind of global optimization solver Exact Algorithm for Maximum Feasible Subsystem Problems with Uncertain Input Data Facial Reduction for Semidefinite Relaxations of Combinatorial Optimization Problems A Bilevel Mixed-Integer Program for the Define-Combine Redistricting Procedure Quadratic Combinatorial Optimization: A Polyhedral Characterization of Linearizable Instances The minimum feedback arc set problem over bidirectional graphs with an application to faculty hiring networks Performance Benchmarks of Quantum Annealing Hardware Certification of sums of squares via low-rank optimization
Combined heat and power systems	Optimizing design and dispatch of a renewable energy system with combined heat and power
Communication	Efficient Gradient Tracking Algorithmic Framework for Decentralized Optimization
communication complexity	Quantum communication complexity of linear regression
Communication Compression	Stochastic Controlled Averaging for Federated Learning with Communication Compression
Competitive analysis	Online Resource Allocation with Predictions
complexity	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
complexity analysis	Proximal Oracles for Optimization and Sampling
complexity bound	Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
complexity guarantees	A study on two-metric projection methods
Compositional Optimization	ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization
compositionality	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
compressive sensing	Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
compromise decisions	A Coordinated Parallelization Algorithm for Compromise Stochastic Programming
Computation	Efficient Gradient Tracking Algorithmic Framework for Decentralized Optimization Partially observable multi-agent RL with (quasi-)efficiency: The blessing of information sharing
computational learning theory	Provably learning a multi-head attention layer
computational noise
computationally expensive optimization	Stochastic Average Model Methods
computationally tractable	A tractable smart predict-then-optimize algorithm beyond the realizable case
computed tomography	Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
Computer simulation	Surface Mount Technology (SMT) Production Line Scheduling by Computer Simulation and Genetic Algorithm
Concave utility	A Robust Approach to Locating Vaccination Centers for a Pandemic: A Problem Driven by Herd Immunity and Decision-Dependent Utility, with a Solution Framework
condition number	Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
conditional generative model
Conditional gradient method	A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
conditional value-at-risk	Bayesian optimization of risk based on Student-t process and extreme value statistics
Conditional-gradient method	An Inexact Conditional Gradient Method for Constrained Bilevel Optimization
cone programming	Any-dimensional convex sets
Confidence Bounds	A Distribution Optimization Framework for Confidence Bounds of Risk Measures
Conflict Graph	Parallelized Conflict Graph Cut Generation
Conic Linear Optimization	A Review of Quantum Interior Point Methods - pros and cons
Conic mixed-binary sets	Constrained Optimization of Low-rank Functions with Indicator Variables
conic optimization	Cone product reformulation for global optimization Minimal representations of generalized power cones Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
conic programming	New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
conic reformulation	EXPRESS: Automatic Convexity Detection and Transformation to Conic Forms for Nonlinear Optimization
conjugate function	Cone product reformulation for global optimization
conjugate gradient method	An LDLT Quasi-Newton Trust-Region Method
constant stepsize	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Constrained Action Space	Handling Action Space Constraints in Deep Reinforcement Learning
constrained convex optimization	A Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition}
constrained Markov decision processes	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
constrained optimal control	A Fokker-Planck optimal control framework in esophageal cancer
constrained optimization	Deep Learning with Nontrivial Constraints Algorithm NCL for constrained optimization: Overcoming LICQ A Trust Region SQP Algorithm for Equality Constrained Optimization Sequential Quadratic Programming for Noisy Equality Constrained Optimization with Rank-Deficient Jacobians Retrospective Approximation for Stochastic Constrained Problems Using Sequential Quadratic Programming An Inexact Conditional Gradient Method for Constrained Bilevel Optimization Stochastic-Gradient-based Interior-Point Algorithms
constrained policy optimization	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
Constraint Generation	A Data-Driven Multistage Stochastic-Robust Optimization Approach with Temporally Correlated Uncertainty
contact optimization	A filter trust-region continuation method for contact optimization and complementarity problems
contagion analytics	Branch-and-price for prescriptive contagion analytics
content creator incentives	Content Creator Incentives in Recommender Systems
Contention Resolution	Random-order Contention Resolution via Continuous Induction: Tightness for Bipartite Matching under Vertex Arrivals
Contextual bandits	Policy learning without overlap: Pessimism and generalized Bernstein's inequality
contextual optimization	Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective Contextual Stochastic Bilevel Optimization Robust Data-driven Prescriptiveness Optimization A tractable smart predict-then-optimize algorithm beyond the realizable case
Contextual stochastic optimization	Integrated Conditional Estimation-Optimization
Continuous approaches to discrete optimization	A Hierarchy of Nonconvex Continuous Reformulations for Discrete Optimization
continuous optimization	A Quantum-Classical Performance Separation in Nonconvex Optimization
continuous-time analysis	Toward a grand unified theory of accelerations in optimization and machine learning
Contrastive Learning	Efficient Pre-training on Massive Datasets: A Data perspective
control	Learning and Predictions in Power System Frequency Control
Controlled Averaging	Stochastic Controlled Averaging for Federated Learning with Communication Compression
Convergence	Accelerated Gradient Descent via Long Steps
convergence analysis	Random block coordinate descent methods for computing optimal transport and convergence analysis
Convergence Guarantees	[REFEREED PAPER TRACK ONLY] Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF
Convergence lower bound	Understanding the Influence of Directed Networks on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm
Convergence rate analysis	Towards a First-Order Algorithmic Framework for Wasserstein Distributionally Robust Optimization
Convex	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions.
Convex analysis	An Outer Approximation Method for Solving Mixed-Integer Convex Quadratic Programs with Indicators
Convex bodies	Optimal Regularization for a Data Source
convex cooperative game	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Convex hull	Constrained Optimization of Low-rank Functions with Indicator Variables
convex hull pricing	Convex Hull Pricing in Electricity Markets: Evidence from a Large US Market
Convex optimization	Last-iterate convergence for convex function-constrained optimization Toward a grand unified theory of accelerations in optimization and machine learning Min-max-min Optimization with Smooth and Strongly Convex Objectives Convex Inverse Mixed-Integer Linear Programming Dual distributed optimization algorithms for potentially disconnected time-varying networks Beyond Discretization: Learning the Optimal Solution Path Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Convex and Non-Convex Problems A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem Convex Optimization-based Algorithms for Strategic Classification Pricing and Routing Strategy to Maximize Profit in Congested Roads Considering Interactions with Travelers Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization A simple uniformly optimal method without line search for convex optimization Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization
convex quadratic programs	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
Convex relaxation	Convex Relaxation for Fokker-Planck Branch-and-bound for D-Optimality with fast local search and variable-bound tightening
convexification	Solution of disjoint bilinear programs using simplicial branch-and-bound
convexity detection	EXPRESS: Automatic Convexity Detection and Transformation to Conic Forms for Nonlinear Optimization
cooling	Local minima in quantum systems
Coordinate Descent	Tangent Subspace Descent on Quotient Manifolds
Copositive program	Stability Analysis of Discrete-Time Linear Complementarity Systems
Copositive programming	Sensitivity analysis for mixed binary quadratic programming
Correction term	A New Fast Proximal Point Algorithm for Monotone Inclusions
Counterfactual decisions	SEQUENTIAL COUNTERFACTUAL DECISIONS
coupled constraints	Min-Max Problems with Coupled Constraints: Theory and Algorithms
Covariate Uncertainty	Robust Personalized Design via Bayesian Optimization under Covariate Uncertainty
Cover inequalities	Handling polyhedral symmetries with a dedicated Branch&Cut: application to a knapsack variant
COVID-19	Branch-and-price for prescriptive contagion analytics
Cross-docking	Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network
Cross-validation	Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression
cryptography	Adversarial Robustness in the Streaming Model
Cubic binary optimization	Tightening Linear Reformulations of 0-1 Cubic Knapsack Problems with Variable Reordering
cubic regularization of Newton	Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
Cutting plane algorithm	Stability Analysis of Discrete-Time Linear Complementarity Systems Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization
Cutting plane method	Coordinate Partitioning for Difficult Euclidean Max-Sum Diversity Problems
Cutting planes	M-Decomposable Sets in Integer Programming Non-Monotonicity of Branching Rules with respect to Linear Relaxations Electric Vehicle Routing: Subpath-Based Decomposition
Cutting set method	An exact method for a class of robust nonlinear optimization problems
Cutting-planes	Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
Cycle Partitioning
D
D-optimality	Branch-and-bound for D-Optimality with fast local search and variable-bound tightening
Dantzig-Wolfe decomposition	Convex Hull Pricing in Electricity Markets: Evidence from a Large US Market
Data Classification	Wasserstein Robust Classification with Fairness Constraints
Data Envelopment Analysis	Classifying with Uncertain DEA
Data Heterogeneity	Stochastic Controlled Averaging for Federated Learning with Communication Compression
Data sharing	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
data visualization	The Best of Both Worlds - Integrating Python and GAMS
data-driven analysis	Profits or Loss: Installing Electric Vehicle Chargers on Public Parking Lots
Data-driven learning	Mirror descent for multi-armed bandits
data-driven methods	Exploiting Observed Network Behavior for Accelerated Optimal Power Flow
data-driven optimization	Data-driven Decision-making with the Optimization & Machine Learning Toolkit (OMLT) Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment
Data-driven policies	Data-driven Policies for Multistage Stochastic Programming
Data-driven sequential decision making	Data-Driven Structured Reinforcement Learning: Foundations and Practice
Data-driven stochastic programming	Residual-Based Distributionally Robust Optimization with Decision-Dependent Uncertainty
data-driven uncertainty set	Risk-Aware Security-Constrained Unit Commitment
Data-quality	Efficient Pre-training on Massive Datasets: A Data perspective
databases	The Best of Both Worlds - Integrating Python and GAMS
DC power flow	Intertemporal Uncertainty Management in Gas-Electric Energy Systems using Stochastic Finite Volumes
DC Programming	Boosted Difference of Convex Algorithms for Clustering with Constraints Algorithms for DC Programming via Polyhedral Approximations of Convex Functions
DCA
Decentralized and Networked Gradient Algorithm	Decentralized and Networked Policy Gradient for Solving Markov Potential Games
decentralized averaging	On graph sequences with finite-time consensus
Decentralized optimization	On the use of the finite-time consensus property in decentralized optimization Dual distributed optimization algorithms for potentially disconnected time-varying networks Efficient Gradient Tracking Algorithmic Framework for Decentralized Optimization Understanding the Influence of Directed Networks on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm
Decision Diagrams	Value Function Projections for Discrete Bilevel Optimization A Single-Level Reformulation of Integer Bilevel Programs using Decision Diagrams
decision rules	Nonlinear Decision Rules Made Scalable by Nonparametric Liftings Risk-Adaptive Local Decision Rules
Decision Tree	A Differentiable Decision Tree Induction Algorithm with Near-optimality
Decision Tree Algorithm	Forecasting Market-Suitable Vegetables by Using a Decision Tree Algorithm
decision trees	Data-driven Decision-making with the Optimization & Machine Learning Toolkit (OMLT)
Decision-dependent uncertainty	A Successive Refinement Algorithm for Stochastic Programs with Decision-Dependent Distribution Functions Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
Decision-focused learning	Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health
Decision-Making and Learning of Agents	Two-Timescale Q-Learning with Function Approximation in Zero-Sum Markov Games
Decision-making with predictions	Online Resource Allocation with Predictions
decomposition	Decomposition and adaptive sampling for data-driven inverse linear optimization
Decomposition algorithms	Optimizing infrastructure system monitoring under stochastic decision-dependent system failures
Deep equilibrium models	Advancing Frontiers in DEQs with Applications in OOD Generalization and Diffusion Models
deep learning	Deep Learning with Nontrivial Constraints Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints Dimension-Free Zeroth-Order Algorithms for Stochastic Programming Under Dimension-Independent Budget Conditions
Deep learning theory	A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks In-context learning of linear functions with gradient descent (an invited talk)
Deep Neural Networks	PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks
Degree theory	Generalizations of R0 and SSM properties for Extended Horizontal Linear Complementarity Problem
DEQ	Advancing Frontiers in DEQs with Applications in OOD Generalization and Diffusion Models
derivative-based optimization	First-order Trust-region Methods with Adaptive Sampling
derivative-free optimization	Branch-and-Model: A Derivative-free Global Optimization Algorithm Stochastic Average Model Methods
Determinant	Determining Sharp Proximity Bounds For Low Row Rank and $\Delta$-Modularity
Diagnostic tools	Diagnostic Tools for Nonlinear Optimization
diagonal linear networks	Linear programming using diagonal linear networks
difference of convex (DC)	Computing a directional stationary solution of DC programs via ADMM
Difference of Convex Functions Algorithm	Boosted Difference of Convex Algorithms for Clustering with Constraints
difference-of-convex optimization	A globally convergent difference-of-convex algorithmic framework and application to log-determinant optimization problems
differentiable optimization	Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization Adaptive Prescriptions for Optimal Power Flow under Uncertainty
differentiable programming	Neuromancer: Differentiable Programming Library for Learning to Optimize and Control Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control
Differential equation	Quantum algorithms for linear differential equations beyond Hamiltonian simulation
differential evolution	Machine learning enhanced meta-heuristic optimization algorithms for autonomous experimentation
Differential Privacy	Impact of Uncertainty on Fairness Nearly Optimal Algorithms for Privately Learning Thresholds and Approximating Median Adversarial Robustness in the Streaming Model Advancements in Differentially Private Stochastic Convex Optimization: Towards Near-Linear Gradient Query Complexity Private Online Prediction from Experts: Separations and Faster Rates
Diffusion models	Advancing Frontiers in DEQs with Applications in OOD Generalization and Diffusion Models Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
dimension insensitive	Dimension-Insensitive Stochastic First-Order Methods for Nonconvex Optimization
Dimension reduction
dimensionality	New Sample Complexity Bounds for (Regularized) Sample Average Approximation in Several Heavy-Tailed, Non-Lipschitzian, and High-Dimensional Cases
Direct-search algorithms	Stochastic derivative-free optimization algorithms using random subspace strategies
directed max cut	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams
directional stationary solution	Computing a directional stationary solution of DC programs via ADMM
Discontinuous Galerkin	A Discontinuous Galerkin Method for Optimal Control Problem of the Obstacle Problem
discrete	On the structure of the inverse-feasible region of a multiobjective integer program
Discrete choice model	Pricing and Routing Strategy to Maximize Profit in Congested Roads Considering Interactions with Travelers
Discrete optimization	Value Function Projections for Discrete Bilevel Optimization Stochastic Scheduling: Strategies for Abandonment Management Discrete Optimization: A Quantum Revolution?
discrete-time Markov chains	Learning Discrete-Time Markov Chains from Aggregate Data
Disjunctive constraints	Dealing with disjunctive constraints in convex mixed-integer nonlinear programming: Efficient formulations and strong cuts
Disjunctive cuts	Sparse multi-term disjunctive cuts for the epigraph of a function of binary variables
Disjunctive programming	Dealing with disjunctive constraints in convex mixed-integer nonlinear programming: Efficient formulations and strong cuts
distributed optimization	A distributed algorithm for multi-scale multi-stage stochastic programs with applications to electricity capacity expansion [REFEREED PAPER TRACK ONLY] Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF On the use of the finite-time consensus property in decentralized optimization On graph sequences with finite-time consensus Adaptive Federated Learning with Auto-Tuned Clients Problem-dependent convergence analysis for randomized linear gradient compression Understanding the Influence of Directed Networks on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm
Distributed Quantum Computing	Divide and conquer approach for distributed quantum computing
Distributed system	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
Distribution Shift	f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
distribution-free algorithms	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
distributional convergence	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Distributional robustness	On the Foundation of Distributionally Robust Reinforcement Learning
Distributional-robustness	A Robust Approach to Locating Vaccination Centers for a Pandemic: A Problem Driven by Herd Immunity and Decision-Dependent Utility, with a Solution Framework
Distributionally Robust	The Terminator: An Integration of Inner and Outer Approximations for Solving Regular and Distributionally Robust Chance Constrained Programs via Variable Fixing
Distributionally Robust Optimization	Robust Data-driven Prescriptiveness Optimization Wasserstein Regularization for 0-1 Loss Decision-making with Side Information: A Causal Transport Robust Approach Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization Wasserstein Robust Classification with Fairness Constraints Chance-Constrained Fractional Programming under Ambiguity -- Distributionally Robust Maximization of Ratio Exceedance Probability Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets Adversarially Robust Optimal Control with Causal Transport Distance Residual-Based Distributionally Robust Optimization with Decision-Dependent Uncertainty
Diversity	Enhancing the Diversity in Language Model Assisted Fundraising
docker	Model Deployment with GAMS Engine
Domain adaptation	In-context learning of linear functions with gradient descent (an invited talk)
Doubly-nonnegative relaxation	A Peaceman-Rachford Splitting Method for the Protein Side-Chain Positioning Problem
dual certificates for IP	Compressing Branch-and-Bound Trees
Dual Decomposition	Branching in the Dual Decomposition Method for Stochastic Integer Programs
Dual degeneracy	Efficient relax-and-cut separation in a branch-and-cut solver
Duality	M-Decomposable Sets in Integer Programming Dual distributed optimization algorithms for potentially disconnected time-varying networks Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints Computational and duality properties of Hoffman constants Binary Integer Program Approximation and the Induced Structural Duality
Duality Theory	Sensitivity analysis for mixed binary quadratic programming Min-Max Problems with Coupled Constraints: Theory and Algorithms
dynamic constraints	Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness
Dynamic Optimal Transport	Improving Autoencoder Image Interpolation via Dynamic Optimal Transport
dynamic programming	Unit Commitment without Commitment: A Dynamic Framework for Managing an Integrated Energy System Under Uncertainty Adaptive Experimentation at Scale Branch-and-price for prescriptive contagion analytics
dynamic programming principle	On the Foundation of Distributionally Robust Reinforcement Learning
dynamic route choice models	Mixture Model for Contextual Route Choice in Multimodal Transportation Systems
Dynamical systems	How well do learning and dimension reduction methods for nonlinear dynamics generalize?
E
E-Optimal design	Simple Randomized Rounding for Max-Min Eigenvalue Augmentation
Early stopping	Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
edge-based districting	The edge-based contiguous p-median problem with connections to territorial districting
edge-based p-median	The edge-based contiguous p-median problem with connections to territorial districting
Edge-concave relaxation	Edge-concave Underestimators and Relaxations for Deterministic Global Optimization
efficiency	Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment
Efficient formulations	Optimizing design and dispatch of a renewable energy system with combined heat and power
Eigenvalue optimization	Spectral Bundle Methods For Primal And Dual Semidefinite Programs Revisiting Spectral Bundle Methods: Primal-dual (Sub)linear Convergence Rates
Eisenberg-Noe model	Systemic Risk Measures Based On Value-at-Risk
Electric vehicles	Profits or Loss: Installing Electric Vehicle Chargers on Public Parking Lots
electricity markets	Convex Hull Pricing in Electricity Markets: Evidence from a Large US Market
electrified transportation	On the coupling between the scheduling of electrified fleets of buses travel and charging and grid pricing.
Empirical risk minimization	Towards a First-Order Algorithmic Framework for Wasserstein Distributionally Robust Optimization
Encryption	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
end-to-end learning	A Generalizable End-to-End Learning Approach for Global Optimization of Quadratically-Constrained Quadratic Programs Decision-making with Side Information: A Causal Transport Robust Approach Learning to Predict Equilibria in Convex Games
Endogenous uncertainty	A Robust Approach to Locating Vaccination Centers for a Pandemic: A Problem Driven by Herd Immunity and Decision-Dependent Utility, with a Solution Framework
Energy	Unit Commitment without Commitment: A Dynamic Framework for Managing an Integrated Energy System Under Uncertainty
Energy Markets	Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty
Entanglement	First-order methods for quantum entanglement detection
entropy regularization	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
epidemic modeling	Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems
Epidemics	Explicit solutions of the SI and Bass models on random networks
Epigraph	Sparse multi-term disjunctive cuts for the epigraph of a function of binary variables
equilibria	Content Creator Incentives in Recommender Systems
Error Bound Analysis	Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Algorithm Design and Convergence Analysis
error ratio	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
error-bound condition	A Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition}
Euclidean distance matrices
Euclidean Max-Sum Diversity Problems	Coordinate Partitioning for Difficult Euclidean Max-Sum Diversity Problems
Evolutionary game theory	A differential game framework for regulating aberrant signaling pathways in esophageal cancer
evolutionary resistance	A differential game framework for regulating aberrant signaling pathways in esophageal cancer
Exact Algorithm	Exact Algorithm for Maximum Feasible Subsystem Problems with Uncertain Input Data
exact algorithms	Electric Vehicle Routing: Subpath-Based Decomposition
exact linear algebra	Fundamentals of Sparse Exact Linear Algebra
Exact penalty functions	Spectral Bundle Methods For Primal And Dual Semidefinite Programs
Expansion planning	Joint Expansion Planning of Power and Water Distribution Networks
expected value	Properties of Two-Stage Stochastic Multiobjective Linear Programs
Experimental Design	Local Search for Constrained Determinant Maximization
exploration	Policy Mirror Descent Inherently Explores the Action Space
Extended Representations	Minimal representations of generalized power cones
Extra Gradient	Last-Iterate Convergence for Learning in Games
extragradient-based minimax optimization	Optimal Minimax Optimization and Variational Inequalities with Separable Structure
extreme value theory	Bayesian optimization of risk based on Student-t process and extreme value statistics
F
facial reduction	A Peaceman-Rachford Splitting Method for the Protein Side-Chain Positioning Problem Facial Reduction for Semidefinite Relaxations of Combinatorial Optimization Problems
facility location	Modeling Processes of Neighborhood Change
Fairness	Impact of Uncertainty on Fairness On a Fair and Risk-averse Urban Air Mobility Resource Allocation Problem Under Demand and Capacity Uncertainties Learning Fair Policies for Multi-stage Selection Problems from Observational Data Wasserstein Robust Classification with Fairness Constraints Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment Fair Minimum Representation Clustering
fairness in AI	Achieving Group Fairness through Social Welfare Optimization
false active index	A new working set method for nonlinear optimization
False Detection Rate	On the Adversarial Robustness of Benjamini Hochberg
feasibility	Assessing Feasibility With Respect to Stochastic Constraints
feasible method	A feasible method for general convex low-rank SDP problems
feature learning	How do neural nets learn features of "simple" functions A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Federated Bilevel Optimization	SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
Federated Learning	SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models Dual distributed optimization algorithms for potentially disconnected time-varying networks Sparse Random Networks for Communication-Efficient Federated Learning Adaptive Federated Learning with Auto-Tuned Clients Stochastic Controlled Averaging for Federated Learning with Communication Compression SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
filters trust-region	A filter trust-region continuation method for contact optimization and complementarity problems
Financial Ratios	Sectoral portfolio optimization by judicious selection of financial ratios via PCA
Finite element	A Discontinuous Galerkin Method for Optimal Control Problem of the Obstacle Problem
finite sum minimization	Stochastic Average Model Methods
Finite-sum Problem	Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method
finite-time consensus	On the use of the finite-time consensus property in decentralized optimization On graph sequences with finite-time consensus
firer-order methods	A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming
first order algorithms	Convex Inverse Mixed-Integer Linear Programming
first order methods	Learning Discrete-Time Markov Chains from Aggregate Data
first-order method	Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
first-order methods	First-order Methods for Bilevel Optimization Towards a First-Order Algorithmic Framework for Wasserstein Distributionally Robust Optimization Lower Complexity Bounds of First-order Methods for Affinely Constrained Composite Non-convex Problems A NEAR-OPTIMAL METHOD FOR CONSTRAINED COMPOSITE NON-CONVEX NON-SMOOTH PROBLEMS Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia
First-order stochastic approximation	On Penalty Methods for Bilevel Optimization
Fixed Charge Network Flow	A Compact Formulation for Dense Fixed-Charge Network Flow Problems
flexible resource allocation	Flexible Resource Job Scheduling - A Mixed Integer Programming Approach
Fokker-Planck	A Fokker-Planck optimal control framework in esophageal cancer
FOM	First-order methods for quantum entanglement detection
Food Losses	Forecasting Market-Suitable Vegetables by Using a Decision Tree Algorithm
Forward-Backward Algorithm	Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
Fractal-Fractional	Bayesian Strategies for Numerical Solutions in Nonlinear Fractional Order Systems: A Focus on Cutaneous Leishmaniasis
Fractional constraint	Chance-Constrained Fractional Programming under Ambiguity -- Distributionally Robust Maximization of Ratio Exceedance Probability
frame interpolation	Improving Autoencoder Image Interpolation via Dynamic Optimal Transport
Frank-Wolfe	A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach: Part II A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach Tensor completion via integer optimization Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe
free spectrahedra	Any-dimensional convex sets
freight logistics	Backhaul Profit Maximization with Multiple Vehicles
Fully polynomial time approximation scheme	Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints
Function-constrained optimization	Last-iterate convergence for convex function-constrained optimization
Fundraising	Enhancing the Diversity in Language Model Assisted Fundraising
G
GAGAN Algorithm(GA)	A Novel Population Based Optimization Approach: GAGAN Algorithm for Traveling Salesman Problem
Game Theory	Who Plays First? Partially observable multi-agent RL with (quasi-)efficiency: The blessing of information sharing When Simple is (Near)-Optimal in Security Games for Urban Transportation
gas pipeline network	Intertemporal Uncertainty Management in Gas-Electric Energy Systems using Stochastic Finite Volumes
gas-electric integrated system	Intertemporal Uncertainty Management in Gas-Electric Energy Systems using Stochastic Finite Volumes
Gauges	SEQUENTIAL COUNTERFACTUAL DECISIONS
Gaussian process	Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness Towards Non-stationary Bayesian Nonparametrics
Gaussian Variational Inference	Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
Generalization	PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization How well do learning and dimension reduction methods for nonlinear dynamics generalize? In-context learning of linear functions with gradient descent (an invited talk) In-Context Convergence of Transformers Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization Generalization Performances in Nonconvex Minimax Optimization: A Comprehensive Study
generalization guarantees	Accelerating Non-Convex Optimization via Learned Sequential Convexifications
Generalized convexity	Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints
Generalized eigenvalue	A new path tracking algorithm for solving the CDT subproblem
Generalized quasiconvexity	Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints
Generation Expansion Planning	Adaptive Multistage Stochastic Programming
generative adversarial network	Towards Provable Gradient Descent Ascent Dynamics in Hidden Structure
generative model	Integration of Machine Learning and Genetic Algorithm as a Generative Model
genetic algorithm	Integration of Machine Learning and Genetic Algorithm as a Generative Model Surface Mount Technology (SMT) Production Line Scheduling by Computer Simulation and Genetic Algorithm
gentrification	Modeling Processes of Neighborhood Change
Geodesic Optimization	Non-convex geodesic optimization for the Paulsen problem in Frame Theory
global convergence	Stochastic Gradient Succeeds for Bandits First-order Methods for Robust Markov Decision Process
Global optimization	A Hierarchy of Nonconvex Continuous Reformulations for Discrete Optimization Hexaly, a new kind of global optimization solver Enabling Scale-up through Multi-fidelity Adaptive Computing Edge-concave Underestimators and Relaxations for Deterministic Global Optimization Branching Adaptive Surrogate Search Method for High-dimensional Optimization Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs Algorithms for DC Programming via Polyhedral Approximations of Convex Functions Exploring Nonlinear Distance Metrics for Lipschitz Constant Estimation in Lower Bound Construction for Global Optimization
Global search	Branch-and-Model: A Derivative-free Global Optimization Algorithm
Gomory corner relaxation	Inverse of the Gomory Corner Relaxation of Integer Programs
Gomory group relaxation	Determining Sharp Proximity Bounds For Low Row Rank and $\Delta$-Modularity
Gomory mixed integer cuts	Efficient relax-and-cut separation in a branch-and-cut solver
GPU	A Differentiable Decision Tree Induction Algorithm with Near-optimality Scalable, high performance linear solvers for nonlinear constrained optimization problems
gradient descent	How do neural nets learn features of "simple" functions Parsimonious Trajectories in Gradient Descent: Emerging Low-dimensionality in Over-parameterized Models Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction A Quantum-Classical Performance Separation in Nonconvex Optimization Accelerated Gradient Descent via Long Steps
gradient descent ascent dynamics	Towards Provable Gradient Descent Ascent Dynamics in Hidden Structure
gradient norm minimization	Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization
Graph Centrality
graph neural networks	CyberTransfer: A Transfer Learning Approach for Enhancing Graph Neural Networks for Intrusion Detection
graph partitioning	A Bilevel Mixed-Integer Program for the Define-Combine Redistricting Procedure
graph scattering	A Generalizable End-to-End Learning Approach for Global Optimization of Quadratically-Constrained Quadratic Programs
Graph Smoothness	Maximizing and Satisficing in Multi-armed Bandits with Graph Information
Graph theory	The minimum feedback arc set problem over bidirectional graphs with an application to faculty hiring networks
graphics processing unit	cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia Accelerated Nonlinear Programming on GPUs: Implementing Solver and Automatic Differentiation
graphons	Any-dimensional convex sets
Graver bases	A Quantum Inspired Bi-level Optimization Algorithm for the First Responder Network Design Problem
ground state	Local minima in quantum systems
group parity	Achieving Group Fairness through Social Welfare Optimization
Grover's algorithm	Discrete Optimization: A Quantum Revolution?
Grunwald Letnikov Finite Difference	Bayesian Strategies for Numerical Solutions in Nonlinear Fractional Order Systems: A Focus on Cutaneous Leishmaniasis
H
Hamilton-Jacobi-Bellman equation	Neural Network Approaches for Parameterized Optimal Control
Hamiltonian simulation	Quantum algorithms for linear differential equations beyond Hamiltonian simulation
Hausdorff convergence	Systemic Risk Measures Based On Value-at-Risk
Health Care Disparities	Quantify Childbirth Care Inequity for Socioeconomically Disadvantaged Groups
Health Care Quality	Quantify Childbirth Care Inequity for Socioeconomically Disadvantaged Groups
Healthcare	Adaptive Optimization and Safe Reinforcement for Heparin Doseing
healthcare analytics	Improving Patient Access via Primary Care Optimization
heavy-tailed-ness	New Sample Complexity Bounds for (Regularized) Sample Average Approximation in Several Heavy-Tailed, Non-Lipschitzian, and High-Dimensional Cases
Herd-immunity	A Robust Approach to Locating Vaccination Centers for a Pandemic: A Problem Driven by Herd Immunity and Decision-Dependent Utility, with a Solution Framework
heuristic	Performance Benchmarks of Quantum Annealing Hardware
Heuristics	A Cycle Cancelling Heuristic for The Traveling Salesman Problem
Hicksian demand	Hicksian Unit-Demand Pricing
Hidden Convexity	Hidden convexity, optimization, and algorithms on rotation matrices
high dimensional	Neural Network Approaches for Parameterized Optimal Control
high dimensional asymptotics	A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
high dimensionality	Dimension-Free Zeroth-Order Algorithms for Stochastic Programming Under Dimension-Independent Budget Conditions
high probability	Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
High-dimension	Branching Adaptive Surrogate Search Method for High-dimensional Optimization
high-dimensional competition	Content Creator Incentives in Recommender Systems
high-dimensional sampling	Proximal Oracles for Optimization and Sampling
High-dimensional statistics	Gain Confidence, Reduce Disappointment: A New Approach to Cross-Validation for Sparse Regression
high-probability guarantees	A Stochastic GDA Method with Backtracking for Solving Nonconvex (Strongly) Concave Minimax Problems High probability and risk-averse guarantees for stochastic saddle point problems
Higher-order Methods	A Higher-Order Interior Point Method for Semidefinite Optimization Problems Failing Strict Complementarity Condition
Hilbert bases	Integer Points in Convex Cones: The Case of PSD and SOC
hindsight optimization	Hindsight Learning for MDPs with Exogenous Inputs
Hoffman constants	Computational and duality properties of Hoffman constants
homelessness	Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment
Hurricane relief logistics	Multi-stage stochastic programming for integrated hurricane relief logistics and evacuation planning
hybrid control	Optimization in hybrid controlled systems with piecewise-smooth systems' dynamics.
hybrid limit cycles	Optimization in hybrid controlled systems with piecewise-smooth systems' dynamics.
hypergradient estimation	Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions
hypomonotonicity	Solving nonmonotone inclusions and Application to nonconvex QP with equality constraints
Hypothesis Testing	On the Adversarial Robustness of Benjamini Hochberg
I
Identical-interest Markov games	Optimistic Policy Iteration In Linearly-Solvable Multi-Agent Games
implicit constraints
implicit equality	Computing implicit equalities of a linear inequality system
implimentation improvement	New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
importance sampling	Self-Structured Importance Sampling for Chance-Constrained Optimization
in-context learning	In-Context Convergence of Transformers
independence number	A Semidefinite Hierarchy for Expected Independence Numbers of Random Graphs
Independent Branching	Building Formulations for Combinatorial Disjunctive Constraints via Biclique Covers
Indicator variables	Constrained Optimization of Low-rank Functions with Indicator Variables
Inertial extrapolation	A New Fast Proximal Point Algorithm for Monotone Inclusions
Inexact Function	LINE-SEARCH BASED OPTIMIZATION USING FUNCTION APPROXIMATIONS WITH TUNABLE ACCURACY
Inexact Gradient	LINE-SEARCH BASED OPTIMIZATION USING FUNCTION APPROXIMATIONS WITH TUNABLE ACCURACY
Inexact Oracle	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
information basis
Integer and Disjunctive Optimization	Distributionally Ambiguous Multistage Stochastic Integer and Disjunctive Programs: Applications to Sequential Two-player Network Interdiction Games
Integer Linear Programming	Package Queries for Massive-scale In-Database Decision Support Chance-Constrained Set k-Covering Problem
integer optimization	Online Rack Placement in Large-scale Data Centers Electric Vehicle Routing: Subpath-Based Decomposition
Integer Points	Integer Points in Convex Cones: The Case of PSD and SOC
integer program	Determining Sharp Proximity Bounds For Low Row Rank and $\Delta$-Modularity Submodular Dispatching with Multiple Vehicles Binary Integer Program Approximation and the Induced Structural Duality
integer programming	On Integer Programs with Irrational Data Inverse of the Gomory Corner Relaxation of Integer Programs Relaxation and Duality for Multiobjective Integer Programming M-Decomposable Sets in Integer Programming Tensor completion via integer optimization A branch-and-bound framework to solve a general class of three-stage interdiction games Backhaul Profit Maximization with Multiple Vehicles Recycling Valid Inequalities for Robust Optimization Parallelized Conflict Graph Cut Generation Branch-and-Bound with Predictions for Variable Selection Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network On the coupling between the scheduling of electrified fleets of buses travel and charging and grid pricing. Fair Minimum Representation Clustering A Cycle Cancelling Heuristic for The Traveling Salesman Problem A Single-Level Reformulation of Integer Bilevel Programs using Decision Diagrams
Interdependent infrastructure networks	Joint Expansion Planning of Power and Water Distribution Networks
Interdiction	A branch-and-bound framework to solve a general class of three-stage interdiction games
interior methods	Algorithm NCL for constrained optimization: Overcoming LICQ
Interior point	A new path tracking algorithm for solving the CDT subproblem
interior point method	On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization Solving Tall Dense SDPs in the Current Matrix Multiplication Time Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs An infeasible interior-point arc-search algorithm for spacecraft trajectory optimization New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
Interior Point Method (IPM)	A Review of Quantum Interior Point Methods - pros and cons
Interior Point Methods	A Higher-Order Interior Point Method for Semidefinite Optimization Problems Failing Strict Complementarity Condition
interior-point method	Accelerated Nonlinear Programming on GPUs: Implementing Solver and Automatic Differentiation
Intermediate Public Transport	When Simple is (Near)-Optimal in Security Games for Urban Transportation
interpretability	Applications of 0-1 Neural Networks in Prescription and Prediction
intrusion detection	CyberTransfer: A Transfer Learning Approach for Enhancing Graph Neural Networks for Intrusion Detection
inverse	On the structure of the inverse-feasible region of a multiobjective integer program
inverse optimization	Inverse of the Gomory Corner Relaxation of Integer Programs Convex Inverse Mixed-Integer Linear Programming Decomposition and adaptive sampling for data-driven inverse linear optimization Mixture Model for Contextual Route Choice in Multimodal Transportation Systems
inverse problems	Fast iterative solvers for initial value control problems with application to diffeomorphic image registration
irrational parameters	On Integer Programs with Irrational Data
ising model	Accelerating Continuous Variable Coherent Ising Machines via Momentum Performance Benchmarks of Quantum Annealing Hardware
Ising Solvers	Benchmarking the Operation of Quantum Heuristics and Ising Machines: Scoring Parameter Setting Strategies on Optimization Applications
Iteration Complexity	A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
iterative methods	Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient
Iterative Refinement	Scalable, high performance linear solvers for nonlinear constrained optimization problems Iterative Refinement for Semidefinite Optimization
J
Jensen's Inequality	A Successive Refinement Algorithm for Stochastic Programs with Decision-Dependent Distribution Functions
Job Scheduling	Stochastic Scheduling: Strategies for Abandonment Management
K
k shortest paths	Designing Resilient Relay Logistics Networks Using k Shortest Paths
KKT conditions	Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
KKT system	Proximal OA method for solving nonconvex MIQCQP
KL property	Local convergence of a sequential quadratic programming method for a class of nonsmooth nonconvex objectives
Knapsack	Tightening Linear Reformulations of 0-1 Cubic Knapsack Problems with Variable Reordering
Knapsack problem	Discrete Optimization: A Quantum Revolution?
Kronecker product	A new path tracking algorithm for solving the CDT subproblem
L
Lagrange multipliers	Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization
Lagrange Relaxation	Solving an Advanced Available-to-Promise (AATP) Problem by Optimization and Meta-heuristics Techniques
Lagrangian duality	Relaxation and Duality for Multiobjective Integer Programming
Lagrangian optimization	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
Lagrangian relaxation	Relaxation and Duality for Multiobjective Integer Programming Backhaul Profit Maximization with Multiple Vehicles Self-Adapting Network Relaxations for Weakly Coupled Markov Decision Processes
Lagrangian underestimate	DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods
Language Model	SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
Large language model	Enhancing the Diversity in Language Model Assisted Fundraising
large scale optimization	Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient
Large-Scale	On the Adversarial Robustness of Benjamini Hochberg
Large-scale optimization	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions.
large-scale stochastic programming	A Coordinated Parallelization Algorithm for Compromise Stochastic Programming
Last-Iterate Convergence	Last-iterate convergence for convex function-constrained optimization Last-Iterate Convergence for Learning in Games
LDLT factorization	An LDLT Quasi-Newton Trust-Region Method
Learning from Experts	Private Online Prediction from Experts: Separations and Faster Rates
Learning in games	Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents Last-Iterate Convergence for Learning in Games Follower Agnostic Methods for Stackelberg Games
Learning Theory	Nearly Optimal Algorithms for Privately Learning Thresholds and Approximating Median
learning to control	Neuromancer: Differentiable Programming Library for Learning to Optimize and Control Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control
learning to optimize	Neuromancer: Differentiable Programming Library for Learning to Optimize and Control Accelerating Non-Convex Optimization via Learned Sequential Convexifications Towards Constituting Mathematical Structures for Learning to Optimize Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control Symbolic Learning to Optimize
least majorized element	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Leontief matrices	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
Level set	A Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition}
leverage scores	Computing Approximate $\ell_p$ Sensitivities
LICQ	Algorithm NCL for constrained optimization: Overcoming LICQ
Lifting	Nonlinear Decision Rules Made Scalable by Nonparametric Liftings
line search-free methods	A simple uniformly optimal method without line search for convex optimization
Line-search	Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory LINE-SEARCH BASED OPTIMIZATION USING FUNCTION APPROXIMATIONS WITH TUNABLE ACCURACY
line-search methods	An LDLT Quasi-Newton Trust-Region Method
Linear Complementarity problem	Generalizations of R0 and SSM properties for Extended Horizontal Linear Complementarity Problem
linear complementarity problems	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
linear decision rule
Linear Decision Rules	Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty
linear optimization	Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
Linear optimization with linear and complementary constraints	Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints
linear programming	Random block coordinate descent methods for computing optimal transport and convergence analysis Linear programming using diagonal linear networks A Cycle Cancelling Heuristic for The Traveling Salesman Problem Computing implicit equalities of a linear inequality system Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient Computational and duality properties of Hoffman constants Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia New Developments of ADMM-based Interior Point Methods for Linear Programming and Conic Programming
linear programming relaxation	Higher order graphical models and binary polynomial optimization
linear programs	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
linear regression	Quantum communication complexity of linear regression
Linear Relaxation
linear solvers	Scalable, high performance linear solvers for nonlinear constrained optimization problems
Linear System	Analysis of Quantum Linear System Algorithms for Linear Systems in Tensor Format
Linearizable	Quadratic Combinatorial Optimization: A Polyhedral Characterization of Linearizable Instances
Linearization	Tightening Linear Reformulations of 0-1 Cubic Knapsack Problems with Variable Reordering
Linearly-Solvable Multi-Agent Games	Optimistic Policy Iteration In Linearly-Solvable Multi-Agent Games
Lipschitz constant estimation	Exploring Nonlinear Distance Metrics for Lipschitz Constant Estimation in Lower Bound Construction for Global Optimization
Lloyd's Algorithm	Fair Minimum Representation Clustering
LNG Portfolio optimization
local convergence	Local convergence of a sequential quadratic programming method for a class of nonsmooth nonconvex objectives
Local Hamiltonian problem	Rigorously Approximating the Local Hamiltonian Problem
Local linear convergence	A linearly convergent Gauss-Newton subgradient method for ill-conditioned problems
local minima	Local minima in quantum systems
Local optima	Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression
Local Ratio	Constrained local Hamiltonians: quantum generalizations of Vertex Cover
Local Search	Local Search for Constrained Determinant Maximization Branch-and-bound for D-Optimality with fast local search and variable-bound tightening
log-barrier smoothing	On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization
Lot Sizing	Adaptive Multistage Stochastic Programming
Lovász theta function	A Semidefinite Hierarchy for Expected Independence Numbers of Random Graphs
low rank	A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach
low-diameter clusters	Integer programming formulations for partitioning a graph into low-diameter clusters
Low-rank functions	Constrained Optimization of Low-rank Functions with Indicator Variables
Low-rank matrix optimization	Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
low-rank matrix recovery	Can Learning Be Explained By Local Optimality In Low-rank Matrix Recovery?
Low-Rank Optimization	A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach: Part II
lower complexity bound	Lower Complexity Bounds of First-order Methods for Affinely Constrained Composite Non-convex Problems
Lyapunov stability	Stability Analysis of Discrete-Time Linear Complementarity Systems
M
machine learning	ABSCORES, Managing Risk and Uncertainty in Electricity Systems Using Banking Scoring and Rating Methodologies Data-driven Decision-making with the Optimization & Machine Learning Toolkit (OMLT) Beyond Discretization: Learning the Optimal Solution Path Problem-dependent convergence analysis for randomized linear gradient compression Integration of Machine Learning and Genetic Algorithm as a Generative Model Forecasting Market-Suitable Vegetables by Using a Decision Tree Algorithm Improving Patient Access via Primary Care Optimization Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization Quantify Childbirth Care Inequity for Socioeconomically Disadvantaged Groups Learning Decision-Focused Uncertainty Sets in Robust Optimization Cost-Optimization of Process-Scale Desalination Systems Incorporating Surrogate-based Water Chemistry Models SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning Residual-Based Distributionally Robust Optimization with Decision-Dependent Uncertainty Neural Embedded Optimization over Sets Stochastic-Gradient-based Interior-Point Algorithms Fair Minimum Representation Clustering Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs
machine learning models	Machine learning enhanced meta-heuristic optimization algorithms for autonomous experimentation
Machine learning safety	Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification
machine scheduling	Flexible Resource Job Scheduling - A Mixed Integer Programming Approach
majorization	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Manifold	Tangent Subspace Descent on Quotient Manifolds
Manifold Optimization	Optimizing AC Power Flow by Exploiting the Power Flow Manifold Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method
margin maximization	Convex Optimization-based Algorithms for Strategic Classification
margin regularization	Wasserstein Regularization for 0-1 Loss
Markov chain	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements Multi-stage stochastic programming for integrated hurricane relief logistics and evacuation planning
Markov Decision Processes	Adaptive Bin Packing with Overflow
Markov Games	Recent advances in computing Nash equilibria in Markov Games Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
Markov Potential Games	Decentralized and Networked Policy Gradient for Solving Markov Potential Games
Markov random fields	On Polynomial-Time Solvability of Combinatorial Markov Random Fields
markovian processes	ABSCORES, Managing Risk and Uncertainty in Electricity Systems Using Banking Scoring and Rating Methodologies
Matching markets	Adaptivity Gaps in Two-sided Assortment Optimization
Mathematical Modeling	Mathematical Modeling in Gravity: Lessons Learned
Mathematical optimization solver	Hexaly, a new kind of global optimization solver
matrix analysis	On graph sequences with finite-time consensus
matrix games	Strategy Investments in Matrix Games
Matroid Intersection	Local Search for Constrained Determinant Maximization
max cut	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams
max-min fairness	Tight Bounds for The Price of Fairness
Maximal monotone	A New Fast Proximal Point Algorithm for Monotone Inclusions
Maximum algebraic connectivity	Simple Randomized Rounding for Max-Min Eigenvalue Augmentation
Maximum clique problem	A Hierarchy of Nonconvex Continuous Reformulations for Discrete Optimization
Maximum Feasible Subsystem Problems	Exact Algorithm for Maximum Feasible Subsystem Problems with Uncertain Input Data
Maximum Load	Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
maximum of d-homogeneous form in d-Holder norm	Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs
measure divergence	Optimization on Measure Spaces with Regular Divergences and Mixed Boundary Conditions
measure space optimization	Optimization on Measure Spaces with Regular Divergences and Mixed Boundary Conditions
Median	Nearly Optimal Algorithms for Privately Learning Thresholds and Approximating Median
Medical Imaging	Federated Hierarchical Tensor Networks: a Collaborative Quantum AI-Driven Framework for Healthcare
Meta Learning	Symbolic Learning to Optimize
Meta-Learning	On First-Order Meta-Reinforcement Learning with Moreau Envelopes
metaheuristic optimization	Machine learning enhanced meta-heuristic optimization algorithms for autonomous experimentation
Metaheuristics	Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network
metal artifacts	Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
Method of multipliers	[REFEREED PAPER TRACK ONLY] Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF
metric subregularity	A superlinearly convergent subgradient method for nonsmooth optimization
MILP
min-max	Min-Max Problems with Coupled Constraints: Theory and Algorithms
Min-max optimization	Last-Iterate Convergence for Learning in Games Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
Min-max-min optimization	Min-max-min Optimization with Smooth and Strongly Convex Objectives
Minimax Optimization	Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Algorithm Design and Convergence Analysis First-order Methods for Bilevel Optimization f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling Generalization Performances in Nonconvex Minimax Optimization: A Comprehensive Study
minimax problems	A Stochastic GDA Method with Backtracking for Solving Nonconvex (Strongly) Concave Minimax Problems High probability and risk-averse guarantees for stochastic saddle point problems
Minimum Enclosing Ellipsoid	Uncertainty Quantification of Set-Membership Estimation in Control and Perception: Revisiting the Minimum Enclosing Ellipsoid
Minimum-Cost Flow	A Cycle Cancelling Heuristic for The Traveling Salesman Problem
Minkowski	M-Decomposable Sets in Integer Programming
MINLP	Mathematical Modeling in Gravity: Lessons Learned Dealing with disjunctive constraints in convex mixed-integer nonlinear programming: Efficient formulations and strong cuts
MIP	A Multiparametric Programming Approach to Accelerate Neural Network based Model Predictive Control Dealing with disjunctive constraints in convex mixed-integer nonlinear programming: Efficient formulations and strong cuts Recent Developments in the Cardinal Optimizer
misspecified case	A tractable smart predict-then-optimize algorithm beyond the realizable case
Mixed binary conic optimization	Learning Fair Policies for Multi-stage Selection Problems from Observational Data
Mixed Binary Quadratic Programming	Sensitivity analysis for mixed binary quadratic programming
Mixed integer linear optimization	Efficient relax-and-cut separation in a branch-and-cut solver Minimal representations of generalized power cones
Mixed Integer Nonlinear Program	Joint Expansion Planning of Power and Water Distribution Networks
Mixed integer programming	Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification A Compact Formulation for Dense Fixed-Charge Network Flow Problems Solving an Advanced Available-to-Promise (AATP) Problem by Optimization and Meta-heuristics Techniques
Mixed-integer linear optimization	Optimizing design and dispatch of a renewable energy system with combined heat and power
Mixed-integer linear programming	Derivation and Generation of Path-Based Valid Inequalities for Transmission Expansion Planning with New Bus Integration
Mixed-Integer Nonlinear Optimization	Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe
Mixed-integer nonlinear programming	An Outer Approximation Method for Solving Mixed-Integer Convex Quadratic Programs with Indicators
Mixed-integer optimization	Who Plays First? Gain Confidence, Reduce Disappointment: A New Approach to Cross-Validation for Sparse Regression Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization On Polynomial-Time Solvability of Combinatorial Markov Random Fields
mixed-integer programming	Data-driven Decision-making with the Optimization & Machine Learning Toolkit (OMLT) Flexible Resource Job Scheduling - A Mixed Integer Programming Approach Mixed-Integer Programming Formulations for Chance-Constrained Optimization with Mixture Models Convex Inverse Mixed-Integer Linear Programming Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Convex and Non-Convex Problems Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks Strategy Investments in Matrix Games Pareto Leap: An Algorithm for Biobjective Mixed-Integer Programming Adaptive Multistage Stochastic Programming Neural Embedded Optimization over Sets Applications of 0-1 Neural Networks in Prescription and Prediction Building Formulations for Combinatorial Disjunctive Constraints via Biclique Covers Non-Monotonicity of Branching Rules with respect to Linear Relaxations
Mixed-integer-biconvex program	A Robust Approach to Locating Vaccination Centers for a Pandemic: A Problem Driven by Herd Immunity and Decision-Dependent Utility, with a Solution Framework
mixture models	Mixed-Integer Programming Formulations for Chance-Constrained Optimization with Mixture Models
Mixture of experts	Mixture Model for Contextual Route Choice in Multimodal Transportation Systems
mobility	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
model refinement	Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness
modeling	The Best of Both Worlds - Integrating Python and GAMS
modeling languages	Automatic Reformulations in AMPL’s New MP Solver Interface Library
Moment-based ambiguity set	Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
Momentum	Advancing SGD: Exploring the Interplay of Stochastic Polyak Step-size and Momentum Accelerating Continuous Variable Coherent Ising Machines via Momentum
Monte Carlo tree search	Efficient Hybrid Simulation Optimization Via Graph Neural Network Metamodeling
Motion Planning	Potential Games on Cubic Splines for Multi-Agent Motion Planning
Motzkin-Straus formulation	A Hierarchy of Nonconvex Continuous Reformulations for Discrete Optimization
MPC	A Multiparametric Programming Approach to Accelerate Neural Network based Model Predictive Control
Multi-Agent	Potential Games on Cubic Splines for Multi-Agent Motion Planning
Multi-agent Games	Optimistic Policy Iteration In Linearly-Solvable Multi-Agent Games Decentralized and Networked Policy Gradient for Solving Markov Potential Games
multi-agent systems	Modeling Processes of Neighborhood Change
Multi-armed bandits	Mirror descent for multi-armed bandits Maximizing and Satisficing in Multi-armed Bandits with Graph Information Adaptive Experimentation at Scale
multi-head attention	Provably learning a multi-head attention layer
multi-objective optimization	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
Multi-stage stochastic programming	Multi-stage stochastic programming for integrated hurricane relief logistics and evacuation planning
Multi-Task Learning	On First-Order Meta-Reinforcement Learning with Moreau Envelopes
Multi-trip vehicle routing	DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods
Multicommodity Flow	A Compact Formulation for Dense Fixed-Charge Network Flow Problems
multicommodity flows	Backhaul Profit Maximization with Multiple Vehicles
multifacility location problem
Multilevel Optimization	A branch-and-bound framework to solve a general class of three-stage interdiction games
multilinear polytope	Higher order graphical models and binary polynomial optimization
Multimodal uncertainty	Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
multiobjective	On the structure of the inverse-feasible region of a multiobjective integer program
Multiobjective optimization	Relaxation and Duality for Multiobjective Integer Programming Pareto Leap: An Algorithm for Biobjective Mixed-Integer Programming SEQUENTIAL COUNTERFACTUAL DECISIONS
Multiparametric Programming	A Multiparametric Programming Approach to Accelerate Neural Network based Model Predictive Control
Multiple Testing	On the Adversarial Robustness of Benjamini Hochberg
Multiradial theory	Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory
Multistage Optimization	Nonlinear Decision Rules Made Scalable by Nonparametric Liftings
Multistage Stochastic Optimization	Adaptive Multistage Stochastic Programming
Multistage stochastic program	A distributed algorithm for multi-scale multi-stage stochastic programs with applications to electricity capacity expansion
multistage stochastic programming	Data-driven Policies for Multistage Stochastic Programming MSPLib and MSPFormat: A Library Of Problems and a New Standardized Data Format For Benchmarking Stochastic Dual Dynamic Programming
N
Nash Equilibria	Recent advances in computing Nash equilibria in Markov Games
Nash equilibrium	Learning to Predict Equilibria in Convex Games A differential game framework for regulating aberrant signaling pathways in esophageal cancer
Near-optimality	A Differentiable Decision Tree Induction Algorithm with Near-optimality
negative curvature	Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm
Nesterov acceleration	Optimal Minimax Optimization and Variational Inequalities with Separable Structure
network	Improved Airline Network Topologies for Building Resilient & Robust Aviation Infrastructures
Network design	Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe Optimization of Bioenergy supply chain for agricultural waste by Considering Environmental Aspects in Ireland
Network Interdiction	Distributionally Ambiguous Multistage Stochastic Integer and Disjunctive Programs: Applications to Sequential Two-player Network Interdiction Games
Network Optimization	Integer programming formulations for partitioning a graph into low-diameter clusters Electric Vehicle Routing: Subpath-Based Decomposition
Network resilience	Designing Resilient Relay Logistics Networks Using k Shortest Paths
Networks
Neural Network	A Multiparametric Programming Approach to Accelerate Neural Network based Model Predictive Control
neural network design	Learning and Predictions in Power System Frequency Control
Neural network verification	Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification
neural networks	Efficient Hybrid Simulation Optimization Via Graph Neural Network Metamodeling Data-driven Decision-making with the Optimization & Machine Learning Toolkit (OMLT) Neural Network Approaches for Parameterized Optimal Control Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization Linear programming using diagonal linear networks Neural Embedded Optimization over Sets Applications of 0-1 Neural Networks in Prescription and Prediction A Quantile Neural Network Framework for Two-stage Stochastic Optimization
Neural tangent kernel	Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
Newton method	Optimization with Superquantile Constraints: A Fast Computational Approach
No-code mathematical optimization	Hexaly, a new kind of global optimization solver
no-regret online learning	No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions
noise estimation
noisy optimization	A Trust Region SQP Algorithm for Equality Constrained Optimization
non-asymptotic analysis	Problem-dependent convergence analysis for randomized linear gradient compression
non-convex	Learning Discrete-Time Markov Chains from Aggregate Data
non-convex non-smooth optimization	Lower Complexity Bounds of First-order Methods for Affinely Constrained Composite Non-convex Problems A NEAR-OPTIMAL METHOD FOR CONSTRAINED COMPOSITE NON-CONVEX NON-SMOOTH PROBLEMS
non-convex optimization	Edge-concave Underestimators and Relaxations for Deterministic Global Optimization Solving Large-Scale Non-convex Optimization Problems in Neural Network Verification Accelerating Non-Convex Optimization via Learned Sequential Convexifications A globally convergent difference-of-convex algorithmic framework and application to log-determinant optimization problems Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
non-convex stochastic optimization	First-order Trust-region Methods with Adaptive Sampling
non-Euclidean nonsmooth distance	Dimension-Insensitive Stochastic First-Order Methods for Nonconvex Optimization
non-interior continuation path	A filter trust-region continuation method for contact optimization and complementarity problems
non-linear conjugate gradient	A differential game framework for regulating aberrant signaling pathways in esophageal cancer
Non-linear cutaneous Leishmaniasis disease model Bayesian Regularization Backpropagation	Bayesian Strategies for Numerical Solutions in Nonlinear Fractional Order Systems: A Focus on Cutaneous Leishmaniasis
Non-linear integer optimization	A Quantum Inspired Bi-level Optimization Algorithm for the First Responder Network Design Problem
non-linear optimization	Exploiting Observed Network Behavior for Accelerated Optimal Power Flow
Non-profit	Enhancing the Diversity in Language Model Assisted Fundraising
Non-smooth Optimization	Advancements in Differentially Private Stochastic Convex Optimization: Towards Near-Linear Gradient Query Complexity Proximal Oracles for Optimization and Sampling
Non-stationarity	Towards Non-stationary Bayesian Nonparametrics
Non-symmetric conic optimization	Recent advances in the COPT conic optimizer
Nonconvex	Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
nonconvex learning	How do neural nets learn features of "simple" functions
nonconvex optimization	Stochastic Lagrangian-based method for nonconvex optimization with nonlinear constraints Parsimonious Trajectories in Gradient Descent: Emerging Low-dimensionality in Over-parameterized Models A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach: Part II Can Learning Be Explained By Local Optimality In Low-rank Matrix Recovery? Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction Cone product reformulation for global optimization A linearly convergent Gauss-Newton subgradient method for ill-conditioned problems A Quantum-Classical Performance Separation in Nonconvex Optimization Exploiting Negative Curvature in Conjunction with Adaptive Sampling: Theoretical Results and a Practical Algorithm Second-Derivative SQP Methods for Nonconvex Nonlinear Optimization Quantum algorithms and software for nonconvex optimization Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization Generalization Performances in Nonconvex Minimax Optimization: A Comprehensive Study
nonconvex quadratic programming	Solving nonmonotone inclusions and Application to nonconvex QP with equality constraints
Nonconvex-concave Problem	Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
Nonconvex-Optimization	On Penalty Methods for Bilevel Optimization
nondominated set	Properties of Two-Stage Stochastic Multiobjective Linear Programs
nonlinear complementarity	A filter trust-region continuation method for contact optimization and complementarity problems
nonlinear distance metrics	Exploring Nonlinear Distance Metrics for Lipschitz Constant Estimation in Lower Bound Construction for Global Optimization
Nonlinear inequality constraints	A new working set method for nonlinear optimization
nonlinear inverse problem	Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction
nonlinear model predictive control	Frequency Recovery in Power Grids using High-Performance Computing
nonlinear optimization	Diagnostic Tools for Nonlinear Optimization Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems Sequential Quadratic Programming for Noisy Equality Constrained Optimization with Rank-Deficient Jacobians O-minimal structures and central paths in nonlinear optimization On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound Tightening Linear Reformulations of 0-1 Cubic Knapsack Problems with Variable Reordering Optimizing AC Power Flow by Exploiting the Power Flow Manifold Fast iterative solvers for initial value control problems with application to diffeomorphic image registration Stochastic-Gradient-based Interior-Point Algorithms Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness An infeasible interior-point arc-search algorithm for spacecraft trajectory optimization
nonlinear programming	Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems Pareto Leap: An Algorithm for Biobjective Mixed-Integer Programming Accelerated Nonlinear Programming on GPUs: Implementing Solver and Automatic Differentiation
nonlinear systems	How well do learning and dimension reduction methods for nonlinear dynamics generalize?
Nonlinearly constrained optimization	Stochastic Lagrangian-based method for nonconvex optimization with nonlinear constraints
nonlocal variational denoising	Transformers Meet Image Denoising: Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals
nonmonotone inclusion	Solving nonmonotone inclusions and Application to nonconvex QP with equality constraints
nonsmooth and nonconvex optimization	A study on two-metric projection methods
Nonsmooth optimization	Last-iterate convergence for convex function-constrained optimization A linearly convergent Gauss-Newton subgradient method for ill-conditioned problems A superlinearly convergent subgradient method for nonsmooth optimization Local convergence of a sequential quadratic programming method for a class of nonsmooth nonconvex objectives
nonstationary inverse problems	Dynamic Parameter Estimation in Deterministic Dynamical Systems
NP-hardness	When Simple is (Near)-Optimal in Security Games for Urban Transportation
Nuclear-norm regularization	Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
number of pivots	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
Numerical analysis	Iterative algorithms for finding phase factors in Quantum signal processing
Numerical Optimization	A Trust Region SQP Algorithm for Equality Constrained Optimization
O
O-minimal structure	O-minimal structures and central paths in nonlinear optimization
OBBT	A Multiparametric Programming Approach to Accelerate Neural Network based Model Predictive Control
Observational data	Learning Fair Policies for Multi-stage Selection Problems from Observational Data
Offline policy learning	Policy learning without overlap: Pessimism and generalized Bernstein's inequality
Online Algorithm	Stochastic Scheduling: Strategies for Abandonment Management
online allocation	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
online learning	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement Convex Optimization-based Algorithms for Strategic Classification Decomposition and adaptive sampling for data-driven inverse linear optimization
Online Matching	Random-order Contention Resolution via Continuous Induction: Tightness for Bipartite Matching under Vertex Arrivals
Online Optimisation	HyperAgent: A Simple, Efficient and Scalable Reinforcement Learning Framework in Complex Environment
Online Optimization	Data-Driven Structured Reinforcement Learning: Foundations and Practice Private Online Prediction from Experts: Separations and Faster Rates
Online resource allocation	Online Resource Allocation with Predictions
Open-source software	Scalable Climate-Aware Power Grid Capacity Expansion using MPI-SPPY
operation complexity	First-order Methods for Bilevel Optimization
operator splitting	Learning to Predict Equilibria in Convex Games
Operator theory	Non-convex geodesic optimization for the Paulsen problem in Frame Theory
Optimal algorithm	Understanding the Influence of Directed Networks on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm
optimal control	Neural Network Approaches for Parameterized Optimal Control Fast iterative solvers for initial value control problems with application to diffeomorphic image registration
Optimal control problems	A Discontinuous Galerkin Method for Optimal Control Problem of the Obstacle Problem
optimal power flow	[REFEREED PAPER TRACK ONLY] Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF Adaptive Prescriptions for Optimal Power Flow under Uncertainty On the coupling between the scheduling of electrified fleets of buses travel and charging and grid pricing. Optimizing AC Power Flow by Exploiting the Power Flow Manifold Frequency Recovery in Power Grids using High-Performance Computing
Optimal transport	Decision-making with Side Information: A Causal Transport Robust Approach Random block coordinate descent methods for computing optimal transport and convergence analysis A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
Optimality conditions	Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints
Optimisation	Optimization of Bioenergy supply chain for agricultural waste by Considering Environmental Aspects in Ireland
optimisation under uncertainty	MSPLib and MSPFormat: A Library Of Problems and a New Standardized Data Format For Benchmarking Stochastic Dual Dynamic Programming
Optimistic Gradient	Last-Iterate Convergence for Learning in Games
optimistic gradient method	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
Optimistic Policy Iteration	Optimistic Policy Iteration In Linearly-Solvable Multi-Agent Games
optimization	Divide and conquer approach for distributed quantum computing Improved Airline Network Topologies for Building Resilient & Robust Aviation Infrastructures Model Deployment with GAMS Engine Iterative algorithms for finding phase factors in Quantum signal processing How well do learning and dimension reduction methods for nonlinear dynamics generalize? Properties of Two-Stage Stochastic Multiobjective Linear Programs Strategy Investments in Matrix Games In-context learning of linear functions with gradient descent (an invited talk) Improving Patient Access via Primary Care Optimization Cost-Optimization of Process-Scale Desalination Systems Incorporating Surrogate-based Water Chemistry Models Hidden convexity, optimization, and algorithms on rotation matrices SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning Recent Developments in the Cardinal Optimizer LINE-SEARCH BASED OPTIMIZATION USING FUNCTION APPROXIMATIONS WITH TUNABLE ACCURACY Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs
Optimization Algorithms	Retrospective Approximation for Stochastic Constrained Problems Using Sequential Quadratic Programming Quantum algorithms and software for nonconvex optimization
Optimization Approach	A Novel Population Based Optimization Approach: GAGAN Algorithm for Traveling Salesman Problem
optimization of risk	Bayesian optimization of risk based on Student-t process and extreme value statistics
Optimization software	Quantum algorithms and software for nonconvex optimization
optimization solver	Deep Learning with Nontrivial Constraints
optimization under decision-dependent uncertainty	Residual-Based Distributionally Robust Optimization with Decision-Dependent Uncertainty
optimization under uncertainty	Intertemporal Uncertainty Management in Gas-Electric Energy Systems using Stochastic Finite Volumes Strategy Investments in Matrix Games Stochastic Scheduling: Strategies for Abandonment Management A Quantile Neural Network Framework for Two-stage Stochastic Optimization
optimization with side information	Contextual Stochastic Bilevel Optimization
OR in energy	Performance Risk Scoring of Risk-free Renewable Generation Bids
out-of-distribution generalization	Advancing Frontiers in DEQs with Applications in OOD Generalization and Diffusion Models
Outer Approximation	Proximal OA method for solving nonconvex MIQCQP Coordinate Partitioning for Difficult Euclidean Max-Sum Diversity Problems
over-parameterization	Parsimonious Trajectories in Gradient Descent: Emerging Low-dimensionality in Over-parameterized Models Can Learning Be Explained By Local Optimality In Low-rank Matrix Recovery?
over-smoothing	Transformers Meet Image Denoising: Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals
Overlap	Policy learning without overlap: Pessimism and generalized Bernstein's inequality
overlap gap property	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
overlapping districting	Districting with Overlapping Service Regions
P
PAC learning	Provably learning a multi-head attention layer
PAC-Bayesian	PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
Parallel Algorithms	Parallelized Conflict Graph Cut Generation
Parallel and Vector Transport Approximation Bounds	Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms
parallel computing	A Coordinated Parallelization Algorithm for Compromise Stochastic Programming Frequency Recovery in Power Grids using High-Performance Computing
parallel optimization	Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems
Parameter Efficient Fine-tuning	SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models
parameter estimation	Data-driven Parameter Estimation for Large-Scale Nonlinear Dynamical Systems
parameter-free	A Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition}
parameter-free methods	A simple uniformly optimal method without line search for convex optimization
parametric optimization	On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization Beyond Discretization: Learning the Optimal Solution Path
Partial differential equation	Convex Relaxation for Fokker-Planck
Partial information	A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing
Partial k-trees
Partially Observability	Partially observable multi-agent RL with (quasi-)efficiency: The blessing of information sharing
particle swarm optimization	Machine learning enhanced meta-heuristic optimization algorithms for autonomous experimentation
Particle Swarm Optimization (PSO)	Solving an Advanced Available-to-Promise (AATP) Problem by Optimization and Meta-heuristics Techniques
PDE constrained optimization	Neural Network Approaches for Parameterized Optimal Control
PDE-constrained optimization	Risk-averse optimization using randomized quasi-Monte Carlo methods Fast iterative solvers for initial value control problems with application to diffeomorphic image registration
PDHG	Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs
Peaceman-Rachford splitting method	A Peaceman-Rachford Splitting Method for the Protein Side-Chain Positioning Problem
Penalty-Methods	On Penalty Methods for Bilevel Optimization
Performance analysis	Data-Driven Structured Reinforcement Learning: Foundations and Practice
Performance Estimation	Accelerated Gradient Descent via Long Steps
personalized healthcare	Applications of 0-1 Neural Networks in Prescription and Prediction
Personalized System Design	Robust Personalized Design via Bayesian Optimization under Covariate Uncertainty
Perspective formulation	Gain Confidence, Reduce Disappointment: A New Approach to Cross-Validation for Sparse Regression
perspective function	Cone product reformulation for global optimization
Perspective functions	Constrained Optimization of Low-rank Functions with Indicator Variables
Pessimism	Policy learning without overlap: Pessimism and generalized Bernstein's inequality
philosophy of modeling	On Integer Programs with Irrational Data
Physics for optimization	On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
pickup and delivery	Backhaul Profit Maximization with Multiple Vehicles
Piecewise linear Relaxations	Building Formulations for Combinatorial Disjunctive Constraints via Biclique Covers
Piecewise Polyhedral Relaxations	Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs
piecewise-smooth dynamics	Optimization in hybrid controlled systems with piecewise-smooth systems' dynamics.
Planning
policy gradient	First-order Methods for Robust Markov Decision Process
policy gradient method	Policy Mirror Descent Inherently Explores the Action Space
policy gradient methods	Constrained Policy Optimization in Reinforcement Learning: A Tale of Regularization and Optimism
Policy learning	Policy learning without overlap: Pessimism and generalized Bernstein's inequality
policy optimization	Robust Data-driven Prescriptiveness Optimization Neural Network Approaches for Parameterized Optimal Control Adaptive Experimentation at Scale Policy learning without overlap: Pessimism and generalized Bernstein's inequality
political redistricting	A Bilevel Mixed-Integer Program for the Define-Combine Redistricting Procedure
Polyak Method	Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Convex and Non-Convex Problems
Polyak-Lojasiewicz condition	Non-convex geodesic optimization for the Paulsen problem in Frame Theory
Polyak-Łojasiewic inequality	Linear convergence of proximal point methods under Polyak-Łojasiewicz and quadratic growth conditions
polyhedra	Computing implicit equalities of a linear inequality system
Polyhedral approximation	Algorithms for DC Programming via Polyhedral Approximations of Convex Functions
Polyhedral study	Handling polyhedral symmetries with a dedicated Branch&Cut: application to a knapsack variant
Polyhedral theory	Inverse of the Gomory Corner Relaxation of Integer Programs
polynomial complexity	Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs
polynomial optimization	AI Hilbert: A New Paradigm for Scientific Discovery by Unifying Data and Background Knowledge Certification of sums of squares via low-rank optimization
Population-based	A Novel Population Based Optimization Approach: GAGAN Algorithm for Traveling Salesman Problem
Portfolio selection	Sectoral portfolio optimization by judicious selection of financial ratios via PCA
Positive Semidefinite Cone	Integer Points in Convex Cones: The Case of PSD and SOC
post-allocation service	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
post-processing quantum algorithms	Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
Potential Games	Potential Games on Cubic Splines for Multi-Agent Motion Planning
Power Distribution Systems	[REFEREED PAPER TRACK ONLY] Convergence Guarantees of a Distributed Network Equivalence Algorithm for Distribution-OPF
power markets	Performance Risk Scoring of Risk-free Renewable Generation Bids
power systems	Exploiting Observed Network Behavior for Accelerated Optimal Power Flow
power systems planning	Frequency Recovery in Power Grids using High-Performance Computing
PPT	First-order methods for quantum entanglement detection
Pre-conditioner	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
Pre-Harvest	Forecasting Market-Suitable Vegetables by Using a Decision Tree Algorithm
Pre-training	Efficient Pre-training on Massive Datasets: A Data perspective
Precedence constraints	Handling polyhedral symmetries with a dedicated Branch&Cut: application to a knapsack variant
Prediction Algorithms
predictions	Learning and Predictions in Power System Frequency Control
prescriptive analytics	Integrated Conditional Estimation-Optimization
price elasticity	Profits or Loss: Installing Electric Vehicle Chargers on Public Parking Lots
price of fairness	Tight Bounds for The Price of Fairness
Pricing	Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty Aggregated Limited-Memory Rank-1 Cuts
pricing policy	Pricing Shared Rides
primal-dual hybrid gradient	Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs
Primal-dual Methods	ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization
Principal component analysis	Sectoral portfolio optimization by judicious selection of financial ratios via PCA
probabilistic graphical models	Higher order graphical models and binary polynomial optimization
Probabilistic set covering
Probing	A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing
process tomography	Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
Programming: Stochastic	Minimum Cost Adaptive Submodular Cover
progress curves	Assessing Feasibility With Respect to Stochastic Constraints
Progressive hedging	A distributed algorithm for multi-scale multi-stage stochastic programs with applications to electricity capacity expansion
projection-free	Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory A Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition}
Projection-Free Method	Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
Prophet Inequalities	Random-order Contention Resolution via Continuous Induction: Tightness for Bipartite Matching under Vertex Arrivals
proportional fairness	Tight Bounds for The Price of Fairness
Protein structure prediction	A Peaceman-Rachford Splitting Method for the Protein Side-Chain Positioning Problem
prox-linear	Accelerating Non-Convex Optimization via Learned Sequential Convexifications
Proximal	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions.
Proximal algorithms
proximal bundle method	Proximal Oracles for Optimization and Sampling
proximal gradient	Stochastic FISTA with fully adapative step sizes.
Proximal method	A distributed algorithm for multi-scale multi-stage stochastic programs with applications to electricity capacity expansion PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks
Proximal point algorithm	A New Fast Proximal Point Algorithm for Monotone Inclusions
proximal point method	Linear convergence of proximal point methods under Polyak-Łojasiewicz and quadratic growth conditions Proximal Oracles for Optimization and Sampling
Proximity	Determining Sharp Proximity Bounds For Low Row Rank and $\Delta$-Modularity
pruning	Sparse Random Networks for Communication-Efficient Federated Learning
Pure Exploration	Maximizing and Satisficing in Multi-armed Bandits with Graph Information
Python	The Best of Both Worlds - Integrating Python and GAMS AMPLS Solver Libraries
Q
Q-Learning	Two-Timescale Q-Learning with Function Approximation in Zero-Sum Markov Games
qaoa	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
QCQP	Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs
QCQPs	A Generalizable End-to-End Learning Approach for Global Optimization of Quadratically-Constrained Quadratic Programs
QIS	First-order methods for quantum entanglement detection
Quadratic Assignment	Quadratic Combinatorial Optimization: A Polyhedral Characterization of Linearizable Instances
Quadratic assignment problem	An interesting generalization of the Koopman-Beckmans quadratic assignment problem
Quadratic constraints	Proximal OA method for solving nonconvex MIQCQP
Quadratic Convergence	Iterative Refinement for Semidefinite Optimization
Quadratic growth	Linear convergence of proximal point methods under Polyak-Łojasiewicz and quadratic growth conditions
Quadratic Minimum Spanning Tree	Quadratic Combinatorial Optimization: A Polyhedral Characterization of Linearizable Instances
quadratic programming	An Outer Approximation Method for Solving Mixed-Integer Convex Quadratic Programs with Indicators Proximal OA method for solving nonconvex MIQCQP A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming
quadratically constrained quadratic programs	A Generalizable End-to-End Learning Approach for Global Optimization of Quadratically-Constrained Quadratic Programs
quantum	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
quantum advantages	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams
Quantum algorithm	Iterative algorithms for finding phase factors in Quantum signal processing A Quantum-Classical Performance Separation in Nonconvex Optimization Quantum algorithms for linear differential equations beyond Hamiltonian simulation
quantum algorithms	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms Quantum Algorithms for Scientific Computation and Optimization Problems Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling
Quantum annealing	Optimization Applications as Quantum Performance Benchmarks A Quantum Inspired Bi-level Optimization Algorithm for the First Responder Network Design Problem Performance Benchmarks of Quantum Annealing Hardware
Quantum Approximate Optimization Algorithm	Optimization Applications as Quantum Performance Benchmarks
Quantum Computation	Optimization Applications as Quantum Performance Benchmarks Local minima in quantum systems
Quantum Computing	Divide and conquer approach for distributed quantum computing Benchmarking the Operation of Quantum Heuristics and Ising Machines: Scoring Parameter Setting Strategies on Optimization Applications A Review of Quantum Interior Point Methods - pros and cons Analysis of Quantum Linear System Algorithms for Linear Systems in Tensor Format Quantum Algorithms for Scientific Computation and Optimization Problems Performance Benchmarks of Quantum Annealing Hardware Quantum algorithms and software for nonconvex optimization Quantum communication complexity of linear regression Discrete Optimization: A Quantum Revolution?
Quantum federated learning	Federated Hierarchical Tensor Networks: a Collaborative Quantum AI-Driven Framework for Healthcare
Quantum generalization	Constrained local Hamiltonians: quantum generalizations of Vertex Cover
quantum Hamiltonian descent	A Quantum-Classical Performance Separation in Nonconvex Optimization
quantum information	Rigorously Approximating the Local Hamiltonian Problem Quantum Algorithms for Scientific Computation and Optimization Problems
Quantum Interior Point Method	Iterative Refinement for Semidefinite Optimization
Quantum IPM	A Review of Quantum Interior Point Methods - pros and cons
Quantum machine learning	Federated Hierarchical Tensor Networks: a Collaborative Quantum AI-Driven Framework for Healthcare
quantum optimization	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
quantum query complexity	Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
Quantum simulation	Federated Hierarchical Tensor Networks: a Collaborative Quantum AI-Driven Framework for Healthcare
quantum singular value transformation	Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling
Quantum speedup	On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Quantum tensor networks	Federated Hierarchical Tensor Networks: a Collaborative Quantum AI-Driven Framework for Healthcare
Quantum tunneling	On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Quantum walks	Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
quantum zero-chain method	Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
Quasi convex optimization problems	A New Fast Proximal Point Algorithm for Monotone Inclusions
quasi-Newton methods	An LDLT Quasi-Newton Trust-Region Method
Quasi-optimal error estimates	A Discontinuous Galerkin Method for Optimal Control Problem of the Obstacle Problem
Quasiconvexity	Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression
qubo	Performance Benchmarks of Quantum Annealing Hardware
Query Processing	Package Queries for Massive-scale In-Database Decision Support
R
Rademacher Average	A Unifying Theory for the Reliability of Stochastic Programming Solutions using Compromise Decisions
random block coordinate descent	Random block coordinate descent methods for computing optimal transport and convergence analysis
random graphs	A Semidefinite Hierarchy for Expected Independence Numbers of Random Graphs
random matrices	Problem-dependent convergence analysis for randomized linear gradient compression
random matrix theory	A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Random Networks	Explicit solutions of the SI and Bass models on random networks
randomized quasi-Monte Carlo	Risk-averse optimization using randomized quasi-Monte Carlo methods
Randomized subspace methods	Stochastic derivative-free optimization algorithms using random subspace strategies
Rare events	Self-Structured Importance Sampling for Chance-Constrained Optimization Optimization under Rare Chance Constraints
Re-scaling	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
recommender systems	Content Creator Incentives in Recommender Systems
Rectified relaxation	Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints
Reduced Order Model	LINE-SEARCH BASED OPTIMIZATION USING FUNCTION APPROXIMATIONS WITH TUNABLE ACCURACY
refactorization	Scalable, high performance linear solvers for nonlinear constrained optimization problems
Refereed Papers Only
reformulation	Automatic Reformulations in AMPL’s New MP Solver Interface Library
Reformulation method	Chance-Constrained Fractional Programming under Ambiguity -- Distributionally Robust Maximization of Ratio Exceedance Probability
Reformulation-Linearization Technique	Cone product reformulation for global optimization
Reformulation-perspectification technique	An exact method for a class of robust nonlinear optimization problems
refugee matching	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
Regret analysis	Online Resource Allocation with Predictions
Regularization	Optimal Regularization for a Data Source PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks
regularized regression	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Reinforcement Learning	HyperAgent: A Simple, Efficient and Scalable Reinforcement Learning Framework in Complex Environment On the Foundation of Distributionally Robust Reinforcement Learning Policy Mirror Descent Inherently Explores the Action Space On First-Order Meta-Reinforcement Learning with Moreau Envelopes No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions Handling Action Space Constraints in Deep Reinforcement Learning Efficient and Scalable Reinforcement Learning via Hypermodel Partially observable multi-agent RL with (quasi-)efficiency: The blessing of information sharing Adaptive Optimization and Safe Reinforcement for Heparin Doseing Neural Network Approaches for Parameterized Optimal Control Adaptive Experimentation at Scale Hindsight Learning for MDPs with Exogenous Inputs
Relational database	Package Queries for Massive-scale In-Database Decision Support
Relax-and-cut separation	Efficient relax-and-cut separation in a branch-and-cut solver
relaxation scheme	A differential game framework for regulating aberrant signaling pathways in esophageal cancer
Relay network design	Designing Resilient Relay Logistics Networks Using k Shortest Paths
renewable energy	Optimizing design and dispatch of a renewable energy system with combined heat and power Performance Risk Scoring of Risk-free Renewable Generation Bids
representation theory	Any-dimensional convex sets
Reproducibility	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
resource allocation	Tight Bounds for The Price of Fairness
resource allocation problem	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Resource Augmentation	When Simple is (Near)-Optimal in Security Games for Urban Transportation
Responsible AI	f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
Restless multi-armed bandits	Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health
restricted Gaussian oracle	Proximal Oracles for Optimization and Sampling
Revenue management	Pricing and Routing Strategy to Maximize Profit in Congested Roads Considering Interactions with Travelers
Ride-sourcing services	Pricing and Routing Strategy to Maximize Profit in Congested Roads Considering Interactions with Travelers
Riemannian	Tangent Subspace Descent on Quotient Manifolds
Riemannian Optimization	Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms A feasible method for general convex low-rank SDP problems
Risk Averse	On a Fair and Risk-averse Urban Air Mobility Resource Allocation Problem Under Demand and Capacity Uncertainties
Risk Measures	A Distribution Optimization Framework for Confidence Bounds of Risk Measures Risk-Adaptive Local Decision Rules
risk scoring	Performance Risk Scoring of Risk-free Renewable Generation Bids
risk-averse optimization	Risk-averse optimization using randomized quasi-Monte Carlo methods
risk-aware optimization	Optimization with Superquantile Constraints: A Fast Computational Approach
Risk-sensitive Decision-making	A Distribution Optimization Framework for Confidence Bounds of Risk Measures
Road Safety	When Simple is (Near)-Optimal in Security Games for Urban Transportation
robust combinatorial optimization	Recycling Valid Inequalities for Robust Optimization
Robust Decision Making	Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Algorithm Design and Convergence Analysis
Robust Design	Robust Personalized Design via Bayesian Optimization under Covariate Uncertainty
robust IPM	Solving Tall Dense SDPs in the Current Matrix Multiplication Time
robust Markov decision process	First-order Methods for Robust Markov Decision Process
Robust nonlinear optimization	An exact method for a class of robust nonlinear optimization problems
robust optimization	Min-max-min Optimization with Smooth and Strongly Convex Objectives Relaxation \& Approximation Algorithm for Solving Sparse PCA Under Robust Uncertainty Set Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty Nonlinear Decision Rules Made Scalable by Nonparametric Liftings Adaptive Prescriptions for Optimal Power Flow under Uncertainty Profits or Loss: Installing Electric Vehicle Chargers on Public Parking Lots Learning Decision-Focused Uncertainty Sets in Robust Optimization Risk-Adaptive Local Decision Rules Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs Classifying with Uncertain DEA
Robustness	How well do learning and dimension reduction methods for nonlinear dynamics generalize? On Polynomial-Time Solvability of Combinatorial Markov Random Fields
Rotation Matrices	Hidden convexity, optimization, and algorithms on rotation matrices
roundoff-error-free linear algebra	Fundamentals of Sparse Exact Linear Algebra
Routing and scheduling	Optimizing infrastructure system monitoring under stochastic decision-dependent system failures
S
SaaS	Model Deployment with GAMS Engine
Saddle Point Problem	Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
saddlepoint	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
saddlepoint problem	Sublevel-Set Geometry and the Performance of restarted-PDHG for Linear and Conic Optimization
sample average approximation	A Unifying Theory for the Reliability of Stochastic Programming Solutions using Compromise Decisions New Sample Complexity Bounds for (Regularized) Sample Average Approximation in Several Heavy-Tailed, Non-Lipschitzian, and High-Dimensional Cases Online Rack Placement in Large-scale Data Centers
Sample average approximations
sample complexity	Maximizing and Satisficing in Multi-armed Bandits with Graph Information Policy Mirror Descent Inherently Explores the Action Space First-order Methods for Robust Markov Decision Process Dimension-Insensitive Stochastic First-Order Methods for Nonconvex Optimization Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms
sample-average approximation	Systemic Risk Measures Based On Value-at-Risk
Sampling-free	Optimization under Rare Chance Constraints
sandpile models	Optimization on Measure Spaces with Regular Divergences and Mixed Boundary Conditions
Scalability	Branching Adaptive Surrogate Search Method for High-dimensional Optimization
Scalable Algorithm	Efficient and Scalable Reinforcement Learning via Hypermodel
Scalable approximate optimization	Package Queries for Massive-scale In-Database Decision Support
scale-up	Enabling Scale-up through Multi-fidelity Adaptive Computing
scarce resource allocation	Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment
Scheduling	Surface Mount Technology (SMT) Production Line Scheduling by Computer Simulation and Genetic Algorithm Submodular Dispatching with Multiple Vehicles
Schur-convexity	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
scientific machine learning	Deep Learning with Nontrivial Constraints Neuromancer: Differentiable Programming Library for Learning to Optimize and Control Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control
Score matching	Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
SDP	Mathematical Modeling in Gravity: Lessons Learned First-order methods for quantum entanglement detection
search theory	Risk-Adaptive Local Decision Rules
Second Order Cone	Integer Points in Convex Cones: The Case of PSD and SOC
Second-Derivative Methods	Second-Derivative SQP Methods for Nonconvex Nonlinear Optimization
Second-order conic optimization	Recent advances in the COPT conic optimizer
Second-order Method	Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method
Second-order stochastic dominance	Sectoral portfolio optimization by judicious selection of financial ratios via PCA
Sectoral portfolio optimization	Sectoral portfolio optimization by judicious selection of financial ratios via PCA
securitization	Performance Risk Scoring of Risk-free Renewable Generation Bids
security	Strategy Investments in Matrix Games
Security and Stackelberg Games	When Simple is (Near)-Optimal in Security Games for Urban Transportation
security constrained unit commitment	ABSCORES, Managing Risk and Uncertainty in Electricity Systems Using Banking Scoring and Rating Methodologies
security games	Strategy Investments in Matrix Games
Security-constrained unit commitment	Risk-Aware Security-Constrained Unit Commitment
Semi-algebraic function	O-minimal structures and central paths in nonlinear optimization
Semi-infinite optimization	Optimality analysis and duality conditions for a class of conic semi-infinite program having vanishing constraints
Semi-infinite programming	Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
Semi-Smooth Newton Method	A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
semi-smooth potential	Proximal Oracles for Optimization and Sampling
semi-stochastic gradient methods	Stochastic Average Model Methods
Semidefinite optimization	A Higher-Order Interior Point Method for Semidefinite Optimization Problems Failing Strict Complementarity Condition Linear convergence of proximal point methods under Polyak-Łojasiewicz and quadratic growth conditions Iterative Refinement for Semidefinite Optimization Recent advances in the COPT conic optimizer
semidefinite programming	Convex Relaxation for Fokker-Planck A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach: Part II A Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming Based on a Hybrid Convex-Nonconvex Approach Solving Tall Dense SDPs in the Current Matrix Multiplication Time Accelerated Gradient Descent via Long Steps Facial Reduction for Semidefinite Relaxations of Combinatorial Optimization Problems A Semidefinite Hierarchy for Expected Independence Numbers of Random Graphs Revisiting Spectral Bundle Methods: Primal-dual (Sub)linear Convergence Rates
Semidefinite programming relaxation	Simple Randomized Rounding for Max-Min Eigenvalue Augmentation
Semidefinite programs	Spectral Bundle Methods For Primal And Dual Semidefinite Programs
Semidefinite Relaxations	Uncertainty Quantification of Set-Membership Estimation in Control and Perception: Revisiting the Minimum Enclosing Ellipsoid
semidefinte programming	A feasible method for general convex low-rank SDP problems
Semigroups	Integer Points in Convex Cones: The Case of PSD and SOC
sensitivities	Computing Approximate $\ell_p$ Sensitivities
Sensitivity Analysis	Sensitivity analysis for mixed binary quadratic programming Risk-Adaptive Local Decision Rules Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
Sequential decision making	Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health Adaptive Optimization and Safe Reinforcement for Heparin Doseing
Sequential Decision-Making	A Data-Driven Multistage Stochastic-Robust Optimization Approach with Temporally Correlated Uncertainty
Sequential Decision-making under Uncertainty	HyperAgent: A Simple, Efficient and Scalable Reinforcement Learning Framework in Complex Environment Efficient and Scalable Reinforcement Learning via Hypermodel
sequential quadratic programming	Sequential Quadratic Programming for Noisy Equality Constrained Optimization with Rank-Deficient Jacobians On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization Retrospective Approximation for Stochastic Constrained Problems Using Sequential Quadratic Programming
Sequential sampling	Data-driven Policies for Multistage Stochastic Programming
service systems	Districting with Overlapping Service Regions
Set Covering	Chance-Constrained Set k-Covering Problem
set functions	Neural Embedded Optimization over Sets
set system approximation	Binary Integer Program Approximation and the Induced Structural Duality
Set-Membership Estimation	Uncertainty Quantification of Set-Membership Estimation in Control and Perception: Revisiting the Minimum Enclosing Ellipsoid
Shamir’s secret sharing	Data Storage and Sharing Scheme Based on Double Blockchain and Proxy Re-Encryption
shared rides	Pricing Shared Rides
sharpness	Improving the Geometry of Linear and Conic Optimization Problems for restarted-PDHG
SI model	Explicit solutions of the SI and Bass models on random networks
Side-chain positioning	A Peaceman-Rachford Splitting Method for the Protein Side-Chain Positioning Problem
signaling pathways	A Fokker-Planck optimal control framework in esophageal cancer
Simple bilevel optimization	A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
Simplex methods	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
SimPy	Surface Mount Technology (SMT) Production Line Scheduling by Computer Simulation and Genetic Algorithm
simulation metamodeling	Efficient Hybrid Simulation Optimization Via Graph Neural Network Metamodeling
simulation optimization	First-order Trust-region Methods with Adaptive Sampling
simultaneous optimization	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
sketching	Computing Approximate $\ell_p$ Sensitivities
sliding motion	Optimization in hybrid controlled systems with piecewise-smooth systems' dynamics.
Smooth	An Adaptive Block Proximal ADMM for Weakly Convex, Linearly-Constrained Composite Functions.
Smooth Convex Optimization	Accelerated Gradient Descent via Long Steps
Smooth optimization	Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization
social welfare optimization	Achieving Group Fairness through Social Welfare Optimization
software	Automatic Reformulations in AMPL’s New MP Solver Interface Library
software packages	Fundamentals of Sparse Exact Linear Algebra
Software tools	Diagnostic Tools for Nonlinear Optimization
solver	AMPLS Solver Libraries Recent Developments in the Cardinal Optimizer
spacecraft trajectory design	An infeasible interior-point arc-search algorithm for spacecraft trajectory optimization
sparse PCA	Relaxation \& Approximation Algorithm for Solving Sparse PCA Under Robust Uncertainty Set
sparsity	PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks Sparse Random Networks for Communication-Efficient Federated Learning On Polynomial-Time Solvability of Combinatorial Markov Random Fields Sparse multi-term disjunctive cuts for the epigraph of a function of binary variables Dimension-Free Zeroth-Order Algorithms for Stochastic Programming Under Dimension-Independent Budget Conditions
Spatiotemporal Beamforming	Blind Source Separation with Spatiotemporal Beamforming
spectral bundle method	Revisiting Spectral Bundle Methods: Primal-dual (Sub)linear Convergence Rates
Spectral bundle methods	Spectral Bundle Methods For Primal And Dual Semidefinite Programs
spectral radius of hypergraph	Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs
spectral radius of nonnegative tensor	Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs
spin glass	Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models
SQP	A Trust Region SQP Algorithm for Equality Constrained Optimization
SQP Methods	Second-Derivative SQP Methods for Nonconvex Nonlinear Optimization
Stability	Gain Confidence, Reduce Disappointment: A New Approach to Cross-Validation for Sparse Regression
Stackelberg equilibrium	A differential game framework for regulating aberrant signaling pathways in esophageal cancer
stackelberg games	Who Plays First? Follower Agnostic Methods for Stackelberg Games
Standard polynomial programming	A Hierarchy of Nonconvex Continuous Reformulations for Discrete Optimization
Star bodies	Optimal Regularization for a Data Source
state space relaxations	Electric Vehicle Routing: Subpath-Based Decomposition
stationary point	Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization
statistical learning theory	Integrated Conditional Estimation-Optimization
Statistical mechanics	Convex Relaxation for Fokker-Planck
stochastic algorithms	Stochastic-Gradient-based Interior-Point Algorithms
stochastic approximation	New Sample Complexity Bounds for (Regularized) Sample Average Approximation in Several Heavy-Tailed, Non-Lipschitzian, and High-Dimensional Cases
Stochastic Augmented Lagrangian	Learning Decision-Focused Uncertainty Sets in Robust Optimization
stochastic constraints	Assessing Feasibility With Respect to Stochastic Constraints
Stochastic Convex Optimization	Advancements in Differentially Private Stochastic Convex Optimization: Towards Near-Linear Gradient Query Complexity
stochastic decomposition	A Coordinated Parallelization Algorithm for Compromise Stochastic Programming
Stochastic derivative-free optimization	Stochastic derivative-free optimization algorithms using random subspace strategies
stochastic dominance	Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
stochastic dual dynamic programming	Adversarially Robust Optimal Control with Causal Transport Distance MSPLib and MSPFormat: A Library Of Problems and a New Standardized Data Format For Benchmarking Stochastic Dual Dynamic Programming
stochastic extragradient	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
stochastic first-order methods	Dimension-Insensitive Stochastic First-Order Methods for Nonconvex Optimization
Stochastic Gradient Descent	Advancing SGD: Exploring the Interplay of Stochastic Polyak Step-size and Momentum Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems
stochastic gradient descent ascent	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
stochastic gradient method	Beyond Discretization: Learning the Optimal Solution Path
stochastic gradient methods	Stochastic Average Model Methods
Stochastic mirror descent with biased gradient oracles	Regularization for Adversarial Robust Learning
Stochastic mixed-integer programming	Scalable Climate-Aware Power Grid Capacity Expansion using MPI-SPPY
Stochastic Optimization	Distributionally Ambiguous Multistage Stochastic Integer and Disjunctive Programs: Applications to Sequential Two-player Network Interdiction Games Mirror descent for multi-armed bandits Last-iterate convergence for convex function-constrained optimization A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing Problem-dependent convergence analysis for randomized linear gradient compression Risk-averse optimization using randomized quasi-Monte Carlo methods Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound Efficient and Scalable Reinforcement Learning via Hypermodel Random-order Contention Resolution via Continuous Induction: Tightness for Bipartite Matching under Vertex Arrivals Adaptive Partitioning for Chance-Constrained Problems with Finite Support Exact Algorithm for Maximum Feasible Subsystem Problems with Uncertain Input Data Retrospective Approximation for Stochastic Constrained Problems Using Sequential Quadratic Programming Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method Understanding the Influence of Directed Networks on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm Optimizing infrastructure system monitoring under stochastic decision-dependent system failures Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling Dimension-Free Zeroth-Order Algorithms for Stochastic Programming Under Dimension-Independent Budget Conditions ALEXR: Optimal Single-Loop Algorithms for Convex Finite-Sum Coupled Compositional Stochastic Optimization
stochastic oracle	Stochastic FISTA with fully adapative step sizes.
stochastic oracles	Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
Stochastic Policies	Handling Action Space Constraints in Deep Reinforcement Learning
Stochastic Polyak Stepsize	Advancing SGD: Exploring the Interplay of Stochastic Polyak Step-size and Momentum
Stochastic Programming	Branching in the Dual Decomposition Method for Stochastic Integer Programs A Unifying Theory for the Reliability of Stochastic Programming Solutions using Compromise Decisions Self-Structured Importance Sampling for Chance-Constrained Optimization Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe Adaptive Multistage Stochastic Programming Hindsight Learning for MDPs with Exogenous Inputs A Quantile Neural Network Framework for Two-stage Stochastic Optimization
stochastic sequential quadratic optimization	Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization
Stochastic variational inequalities	Optimal Minimax Optimization and Variational Inequalities with Separable Structure
Stochastic-Robust Optimization	A Data-Driven Multistage Stochastic-Robust Optimization Approach with Temporally Correlated Uncertainty
stochatic policy gradient	Stochastic Gradient Succeeds for Bandits
strategic agents	Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
strategic classification	Convex Optimization-based Algorithms for Strategic Classification
streaming algorithms	An Exponential Quantum Advantage for Approximating Directed Max Cut in Graph Streams
streaming model	Adversarial Robustness in the Streaming Model
Strict Complementarity	A Higher-Order Interior Point Method for Semidefinite Optimization Problems Failing Strict Complementarity Condition
Strong Partitioning	Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs
Structured reinforcement learning	Data-Driven Structured Reinforcement Learning: Foundations and Practice
Student-t process	Bayesian optimization of risk based on Student-t process and extreme value statistics
Sub-gradient	Solving an Advanced Available-to-Promise (AATP) Problem by Optimization and Meta-heuristics Techniques
Subgradient Optimization	Acceleration of Level Adjustment for the Polyak Stepsize: Applications to Convex and Non-Convex Problems
submodular	Submodular Dispatching with Multiple Vehicles
submodular polyhedra	A characterization of simultaneous optimization, majorization, and (bi)submodular polyhedra
Submodularity	On Polynomial-Time Solvability of Combinatorial Markov Random Fields
Successive Refinement Algorithm	A Successive Refinement Algorithm for Stochastic Programs with Decision-Dependent Distribution Functions
sum of squares	Certification of sums of squares via low-rank optimization
Sum-of-squares optimization	AI Hilbert: A New Paradigm for Scientific Discovery by Unifying Data and Background Knowledge
super-linear correction	A new working set method for nonlinear optimization
superadditive duality	Relaxation and Duality for Multiobjective Integer Programming
superlinear convergence	A superlinearly convergent subgradient method for nonsmooth optimization
superlinear local convergence	On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization
superquantile	Optimization with Superquantile Constraints: A Fast Computational Approach
supervalid inequalities	The edge-based contiguous p-median problem with connections to territorial districting
Supervised classification	SEQUENTIAL COUNTERFACTUAL DECISIONS
Supply Chain
Supply chain management	Optimization of Bioenergy supply chain for agricultural waste by Considering Environmental Aspects in Ireland
Surface Mount Technology (SMT)	Surface Mount Technology (SMT) Production Line Scheduling by Computer Simulation and Genetic Algorithm
surrogate modeling	Enabling Scale-up through Multi-fidelity Adaptive Computing
Surrogate Models	Cost-Optimization of Process-Scale Desalination Systems Incorporating Surrogate-based Water Chemistry Models
surrogates	Adaptive Surrogate Modeling for Trajectory Optimization with Model Inexactness
sustainability	Pricing Shared Rides
switching manifolds	Optimization in hybrid controlled systems with piecewise-smooth systems' dynamics.
symbolic analysis	EXPRESS: Automatic Convexity Detection and Transformation to Conic Forms for Nonlinear Optimization
Symbolic Learning	Symbolic Learning to Optimize
symmetry	Any-dimensional convex sets
system design optimization	Co-Design of Complex Systems: From Autonomy to Future Mobility Systems
system identification	How well do learning and dimension reduction methods for nonlinear dynamics generalize?
Systemic risk measure	Systemic Risk Measures Based On Value-at-Risk
T
task-based learning	Adaptive Prescriptions for Optimal Power Flow under Uncertainty
Technoeconomic Analysis	Cost-Optimization of Process-Scale Desalination Systems Incorporating Surrogate-based Water Chemistry Models
Tensor completion	Tensor completion via integer optimization
Tensor Format	Analysis of Quantum Linear System Algorithms for Linear Systems in Tensor Format
tensor optimal transport	Interior point method for tensor optimal transport, spectral radius of nonnegative tensors and hypergraphs
The k-center problem	Min-max-min Optimization with Smooth and Strongly Convex Objectives
Thresholds	Nearly Optimal Algorithms for Privately Learning Thresholds and Approximating Median
Time Series Forecast
Time series models	Multi-stage stochastic programming for integrated hurricane relief logistics and evacuation planning
Time-varying networks	Dual distributed optimization algorithms for potentially disconnected time-varying networks
time-varying parameters	Dynamic Parameter Estimation in Deterministic Dynamical Systems
totally unimodular linear programs	Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs
training dynamics	In-Context Convergence of Transformers
transfer learning	CyberTransfer: A Transfer Learning Approach for Enhancing Graph Neural Networks for Intrusion Detection
transformer	Transformers Meet Image Denoising: Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals In-Context Convergence of Transformers
transformers	Provably learning a multi-head attention layer
Transmission expansion planning	Derivation and Generation of Path-Based Valid Inequalities for Transmission Expansion Planning with New Bus Integration
Transportation planning	Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network
Traveling Salesman Problem	A Cycle Cancelling Heuristic for The Traveling Salesman Problem
Traveling Salesman Problem (TSP)	A Novel Population Based Optimization Approach: GAGAN Algorithm for Traveling Salesman Problem
Trust Region	A Trust Region SQP Algorithm for Equality Constrained Optimization
Trust-region algorithms	Stochastic derivative-free optimization algorithms using random subspace strategies
trust-region methods	An LDLT Quasi-Newton Trust-Region Method
trustworthy AI	Deep Learning with Nontrivial Constraints
Tuning-Free
Two Team zero-sum games	Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
two-layer neural network	Towards Provable Gradient Descent Ascent Dynamics in Hidden Structure
two-metric projection	A study on two-metric projection methods
two-stage optimization	On the Convergence of a Decomposition Algorithm for Nonlinear Two-Stage Optimization
Two-stage stochastic programming	A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing
U
uncertainty	Properties of Two-Stage Stochastic Multiobjective Linear Programs Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty
Unconstrained Binary Nonlinear Programming Problem
Unconstrained minimization	An LDLT Quasi-Newton Trust-Region Method
under-estimators	Edge-concave Underestimators and Relaxations for Deterministic Global Optimization
Uniform Convergence	Generalization Performances in Nonconvex Minimax Optimization: A Comprehensive Study
uniformly optimal methods	A simple uniformly optimal method without line search for convex optimization
Unit Commitment	Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty
Unit commitment problems	Unit Commitment without Commitment: A Dynamic Framework for Managing an Integrated Energy System Under Uncertainty
universal method	Proximal Oracles for Optimization and Sampling
Universal relaxation theory	Rectified Relaxation: A new learning approach for linear optimization with linear and complementary constraints
Urban Air Mobility	On a Fair and Risk-averse Urban Air Mobility Resource Allocation Problem Under Demand and Capacity Uncertainties
V
Valid inequalities	Recycling Valid Inequalities for Robust Optimization Sparse multi-term disjunctive cuts for the epigraph of a function of binary variables Derivation and Generation of Path-Based Valid Inequalities for Transmission Expansion Planning with New Bus Integration
value-at-risk	Systemic Risk Measures Based On Value-at-Risk
Variable fixing	The Terminator: An Integration of Inner and Outer Approximations for Solving Regular and Distributionally Robust Chance Constrained Programs via Variable Fixing DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods
variable-bound tightening	Branch-and-bound for D-Optimality with fast local search and variable-bound tightening
variational inequalities	Learning to Predict Equilibria in Convex Games A Discontinuous Galerkin Method for Optimal Control Problem of the Obstacle Problem Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
variational inequality	Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Vegetable Crops	Forecasting Market-Suitable Vegetables by Using a Decision Tree Algorithm
Vehicle Restraint System	Robust Personalized Design via Bayesian Optimization under Covariate Uncertainty
vehicle routing	Electric Vehicle Routing: Subpath-Based Decomposition
verification tools	Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
Vertex Cover	Constrained local Hamiltonians: quantum generalizations of Vertex Cover
W
Warm-Starts
warped proximal iteration	Solving nonmonotone inclusions and Application to nonconvex QP with equality constraints
Wasserstein Ambiguity Set	Wasserstein Robust Classification with Fairness Constraints
Wasserstein distance-based ambiguity set	Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
Wasserstein distributionally robust optimization	Regularization for Adversarial Robust Learning Towards a First-Order Algorithmic Framework for Wasserstein Distributionally Robust Optimization
Wasserstein metric	Wasserstein Regularization for 0-1 Loss Integer Programming Approaches for Distributionally Robust Chance Constraints with Adjustable Risks
Waste management	Optimization of Bioenergy supply chain for agricultural waste by Considering Environmental Aspects in Ireland
Water Treatment	Cost-Optimization of Process-Scale Desalination Systems Incorporating Surrogate-based Water Chemistry Models
Weakly convex optimization	Linear convergence of proximal point methods under Polyak-Łojasiewicz and quadratic growth conditions
weakly coupled Markov Decision Processes	Self-Adapting Network Relaxations for Weakly Coupled Markov Decision Processes
Weierstrass preparation theorem	O-minimal structures and central paths in nonlinear optimization
Weight Decay	PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks
Whittle index policy	Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health
wind uncertainty	Risk-Aware Security-Constrained Unit Commitment
working index set	A new working set method for nonlinear optimization
workload balancing	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
Worm Optimization (WO)	Worm Optimization Algorithm to Solve for the Transportation Problem of Cross-Docking Network
worst-case complexity	A NEAR-OPTIMAL METHOD FOR CONSTRAINED COMPOSITE NON-CONVEX NON-SMOOTH PROBLEMS
Z
Z-matrices	On the number of pivots of Dantzig's simplex methods for linear and convex quadratic programs
zero-one loss	Wasserstein Regularization for 0-1 Loss
zero-sum game objectives with hidden structure	Towards Provable Gradient Descent Ascent Dynamics in Hidden Structure
zero-sum games	Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling
Zero-Sum Markov Games	Two-Timescale Q-Learning with Function Approximation in Zero-Sum Markov Games
Zeroth-order methods	Stochastic derivative-free optimization algorithms using random subspace strategies
zeroth-order optimization	Follower Agnostic Methods for Stackelberg Games Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms Dimension-Free Zeroth-Order Algorithms for Stochastic Programming Under Dimension-Independent Budget Conditions