2025 ALLERTON: 61ST ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING

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

6
6G	On Secrecy Capacity of Binary Beampointing Channels with Block Memory and Feedback
A
A Priori Optimization	The Sum of Leaf Weights in the Minimum Spanning Tree of the Complete Graph
Abstractions	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS)
Achievable Rates	Z-Channel Modeling of Hardware Trojans
active generative AI	Active Generative Models for Inference and Learning in Complex Physical World
active learning	Learning and predicting uncertain dynamical systems from data Confronting Uncertainty in AI for Science
Adaptive Optimization	Reliable and Adaptive Stochastic Optimization in the Face of Messy Data
Adversarial robustness	Diffusion bridges and adversarial examples
adversarial training	Regionally Robust Autoencoder-Based Channel Codes
Age of Information	Version Age of Information with Contact Mobility in Gossip Networks Optimizing Age of Information without Knowing the Age of Information
Age of Information	Optimal Sampling and Scheduling for Remote Fusion Estimation of Correlated Wiener Processes
agent-based model	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
AI for Science	Confronting Uncertainty in AI for Science
AI-enabled Cyber-Physical Systems	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS)
aleatoric uncertainty	Confronting Uncertainty in AI for Science
Algorithms with predictions	Online Bipartite Matching with Advice
Alpha-mutual information	Exact Channel Simulation under Exponential Cost
Analytical Function Discovery	Analytical Lyapunov Function Discovery: An RL-based Generative Approach
anomaly detection	Cluster-Aware Causal Mixer for Sequential Change Detection in Multivariate Time Series
Approximation Error	A Precise Performance Analysis of the Randomized Singular Value Decomposition
Artificial Intelligence	A Stochastic-Control Lense unifying Transformers, Diffusions & Reinforcement Learning
Artificial neural networks	Soft Training: Method for Neural Network Learning
Artificial parameter	Artificial Parameter Based Approximate Solutions of Non-Symmetric Matrix Riccati Differential Equation
asymmetric channels	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
asymptotic optimality	Dual-Sensor Quickest Change Detection with Sampling Control Optimal Change Detection in Multi-Armed Bandit
atomic norm	Hybrid Atomic Norm Sparse/Diffuse Channel Estimation
Attention	Tensor Product Attention Is All You Need
Autoencoder	Regionally Robust Autoencoder-Based Channel Codes
automation	Automation and generative AI accelerated design of bio-therapeutics
Autonomous systems	Co-Optimization of Perception and Control for Autonomous Systems
Average reward	Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
B
balanced matching	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
batteries	Battery Operations in Electricity Markets: Strategic Behavior and Distortions
Bayesian deep learning	Learning and predicting uncertain dynamical systems from data
Bayesian inference	Failure Prediction from Limited Hardware Demonstrations
Bayesian methods	BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems
Bayesian networks	Ordinal-Poisson Causal Discovery
Bayesian persuasion	Persuasion under Dynamic Trust: Parametric Sender Behavior
Bayesian uncertainty quantification	Learning and predicting uncertain dynamical systems from data
Beamforming	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
Beamspace Processing	Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
binary dot product	Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation
Binning	Source-Channel Coding in Multiple-Access Channels with Correlated Sources
Biometric identification systems	An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources
biosystems design	Automation and generative AI accelerated design of bio-therapeutics
Breakdown Point	A FREQUENTIST THEORY FOR M-POSTERIORS: ASYMPTOTIC AND ROBUSTNESS PROPERTIES
broadcast channel	On Explicit Families of Outer Bounds for Broadcast Networks
broadcast networks	On Explicit Families of Outer Bounds for Broadcast Networks
Budget Constraints	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
C
caching network	Distributed Caching of Transient Contents in a Tandem of Caches
Camera-based Perception	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS)
capacity region	On Explicit Families of Outer Bounds for Broadcast Networks
Catastrophic Forgetting	Learning Without Forgetting
causal discovery	Ordinal-Poisson Causal Discovery
causal inference	Ordinal-Poisson Causal Discovery
causal mixing	Cluster-Aware Causal Mixer for Sequential Change Detection in Multivariate Time Series
chain of thought	Transformers Provably Learn Symbolic Multi-step Reasoning via Chain of Thought
Change Detection	Reinforcement Learning Design for Quickest Change Detection - Extended Abstract
change-point	Optimal Change Detection in Multi-Armed Bandit
Change-point detection	Online Kernel CUSUM for Change-Point Detection
Changepoint detection	A Proof of The Changepoint Detection Threshold Conjecture in Preferential Attachment Models
channel coding	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
channel estimation	Hybrid Atomic Norm Sparse/Diffuse Channel Estimation
Channel simulation	Exact Channel Simulation under Exponential Cost
channel with feedback	On Secrecy Capacity of Binary Beampointing Channels with Block Memory and Feedback
Classification	Soft Training: Method for Neural Network Learning
cloud computing	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud Optimal Service Mode Assignment in a Simple Computation Offloading System
clustering of time series	Joint Problems in Learning Multiple Dynamical Systems
Codec	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
coding techniques and applications	An Upper Bound for Interactive ECCs with Separate Budgets
coding theory	An Upper Bound for Interactive ECCs with Separate Budgets
combination network	On Explicit Families of Outer Bounds for Broadcast Networks
Combinatorial design theory	Maximal Achievable Service Rates of Codes and Connections to Combinatorial Designs
Common randomness	Exact Channel Simulation under Exponential Cost
Communication Systems	Communication Systems with Mismatched Encoder and Decoders
Complete Information	Linear-Quadratic Stackelberg Differential Games for Jump-Diffusion Systems with Complete and Partial Information
complex networked systems	Reliable Inference at Scale Using Graph Structure
Complexity	The Tarski Search Problem: Algorithms, Complexity, and Open Questions
Compositional Verification	Compositional Verification of Autonomous Systems
compressed sensing	Towards an optimal solution to NMF
Compression	Compression for Incentivization
compression	Problem-dependent convergence bounds for randomized linear gradient compression
computation offloading	Optimal Service Mode Assignment in a Simple Computation Offloading System
Computational complexity	Principled Learning-to-Communicate with Quasi-Classical Information Structures
Concentration	Estimating Error in Natural Distribution Estimation
Conditional Value at Risk	Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
Conjectural reasoning	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
consensus	Coordination Games on Multiplex Networks: Consensus and Convergence of Opinion Dynamics
Conservative Q-learning	Learning Neural Control Barrier Functions from Demonstrations
Constellation Design	Joint Constellation and Labeling Design for Gaussian Interference Channels via Autoencoders
constrained Cramer-Rao bound	Hybrid Atomic Norm Sparse/Diffuse Channel Estimation
Constrained Markov Decision Process	Towards a Nudge-Theoretic Cyber Deception Framework
Constraint satisfaction problem	Stochastic model and decomposition schemes for relaxation oscillator based SAT solver
content caching	Distributed Caching of Transient Contents in a Tandem of Caches
Continual Learning	Learning Without Forgetting
contraction theory	On the role of time scale in reservoir computing
contrastive pre-training	Global Minimizers of Sigmoid Contrastive Loss
Control	HardNet: Hard-Constrained Neural Networks
convergence of probability measures	A theoretical basis for model collapse in recursive training
Converses	Information-Theoretic Outer-bounds from Sphere-Packing, Compactness, and Zero-One Laws
convex minorant	Asymptotic convexity of wide and shallow neural networks
convex optimization	Hybrid Atomic Norm Sparse/Diffuse Channel Estimation Watts and Drops: Co-Scheduling Power and Water in Desalination Plants
coordination games	Coordination Games on Multiplex Networks: Consensus and Convergence of Opinion Dynamics
Copositive programming	Pricing in Discrete Markets Using Copositive Duality
coset states	Winning Rates of (n, k) Quantum Coset Monogamy Games
Cost Optimization	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
Counterfactual Retrieval	Private Counterfactual Retrieval
cross technology communications	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
cross-sector partnership	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
CUSUM	Optimal Bounded-Influence Procedure for Robust Sequential Change-Point Detection
cutting-plane methods	A Cutting-plane Method for Semidefinite Programming with Potential Applications on Noisy Quantum Devices
Cyber Deception	Towards a Nudge-Theoretic Cyber Deception Framework
cyber-physical systems	Deception against Game-Theoretic Learning in Complex Adaptive Systems
cyclostationary	Sequential Procedures for Early Detection of Machine Faults
D
data acquisition	Optimal Data Acquisition with Privacy-Aware Agents
data assimilation	FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
Data compression	Synchronizing Probabilities in Model-Driven Compression
data ecology	Toward a Theory of Data Ecology: Understanding and Steering Data Ecosystems
data markets	Optimal Data Acquisition with Privacy-Aware Agents
Data modeling	BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems
data-driven methods	Sequential Change Point Detection via Denoising Score Matching
dataflows	Toward a Theory of Data Ecology: Understanding and Steering Data Ecosystems
day-ahead	Battery Operations in Electricity Markets: Strategic Behavior and Distortions
DC power flow	Optimal Battery Placement in Power Grid
Dec-POMDP	Principled Learning-to-Communicate with Quasi-Classical Information Structures
Decentralized algorithms	Optimal Setpoints of Current Constrained Converters-Based Resources
Decoding	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
Deep Learning	Joint Constellation and Labeling Design for Gaussian Interference Channels via Autoencoders
Deep Neural Network Verification	StarV: A Qualitative and Quantitative Verification Framework for Learning-enabled Autonomy
deep reinforcement learning (DRL)	DPIR: Deep Predictive Interference-Aware Routing for Wireless Networks
delay-optimal control	Optimal Service Mode Assignment in a Simple Computation Offloading System
Delayed engagement decision	Differential Game Based Guidance with Delayed Engagement Decision
demand response	Optimal Mechanisms for Demand Response: An Indifference Set Approach
denoising	Linking Diffusion Models & I-MMSE
denoising score matching	Sequential Change Point Detection via Denoising Score Matching
dependent data	Learning and inference from temporally dependent data
desalination	Watts and Drops: Co-Scheduling Power and Water in Desalination Plants
detection and estimation	Reliable Inference at Scale Using Graph Structure
detection delay	Optimal Change Detection in Multi-Armed Bandit
Differential entropy	Soft Training: Method for Neural Network Learning
Differential game	Differential Game Based Guidance with Delayed Engagement Decision
Differential Privacy	Optimal Data Acquisition with Privacy-Aware Agents On Subset Retrieval and Group Testing Problems with Differential Privacy Constraints
differential privacy	The Role of Private Synthetic Data in Collaborative Learning
Differential Privacy	Leaky Multi-Message Private Information Retrieval with Differential Privacy Guarantees
diffusion	Path-Generalized I-MMSE: Bridging Diffusion and Autoregressive Generation
diffusion model	Editing and inversion of images with flow models DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP
Diffusion Models	Diffusion bridges and adversarial examples Foundation Models for Spatio-temporal Physics Linking Diffusion Models & I-MMSE Distillation learns clean generative models from corrupted data
Directional Modulation	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
discrete distribution estimation	Learning and inference from temporally dependent data
distillation	Distillation learns clean generative models from corrupted data
distributed and large-scale systems	Reliable Inference at Scale Using Graph Structure
Distributed Computing	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
Distributed Energy Resources	Inexactness of Second-order Cone Relaxations for Calculating Operating Envelopes
distributed learning	Sketching for Distributed Deep Learning
distributed optimization	Problem-dependent convergence bounds for randomized linear gradient compression
Distributed Storage Systems	Maximal Achievable Service Rates of Codes and Connections to Combinatorial Designs
Distribution Estimation	Estimating Error in Natural Distribution Estimation
distribution-free algorithms	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
duty cycle constraint	Dual-Sensor Quickest Change Detection with Sampling Control
Dynamic calibration	Error-Sensitive Dynamic Calibration for Online Optimization with Switching Costs
Dynamic information acquisition	On Myopia in Rationally Inattentive Dynamic Information Acquisition
Dynamic mechanism design	Allocating Shared Resources via Dynamic Max-Min Fairness
dynamic scheduling	Optimal Service Mode Assignment in a Simple Computation Offloading System
dynamical systems	Learning and predicting uncertain dynamical systems from data
dynamical systems	When do practical Koopman embeddings exist?
E
echo state networks	On the role of time scale in reservoir computing
electricity	Optimal Mechanisms for Demand Response: An Indifference Set Approach
electricity market	Pricing in Discrete Markets Using Copositive Duality
electricity markets	Battery Operations in Electricity Markets: Strategic Behavior and Distortions
Encoding	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
Energy	Unit Commitment without Commitment: The Network Setting
Energy harvesting wireless networks	Minimum-Latency Reliable Routing in Interference-Powered Networks
Entanglement-assisted communication	Relaying Quantum Information
Entropy coding	Synchronizing Probabilities in Model-Driven Compression
Epidemiological modeling	If the Virus Respected Queues
epistemic uncertainty	Confronting Uncertainty in AI for Science
Equilibrium selection	Learning with Episodic Hypothesis Testing in General Games
ergodic rate	On Estimation of Angles of Arrival in Monostatic ISAC Without Instantaneous Transmit CSI at the Transmiter
Erlang-C	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
Error-correcting codes	Interpreting learned error-correcting codes
Error-sensitive	Error-Sensitive Dynamic Calibration for Online Optimization with Switching Costs
Estimation	Ordinal-Poisson Causal Discovery Estimating Error in Natural Distribution Estimation
Estimation	Focal Loss: Statistical and Information-Theoretic Perspectives
Estimation bias	Experimentation in the Presence of Strategic Buyers: Unbiased Estimation Under Intertemporal Substitution
Evaluation	On Speeding Up Language Model Evaluation
exploration	Reward Biasing in RL: Tempered Optimism for Exploration Improves Performance
Exponential cost	Exact Channel Simulation under Exponential Cost
externality	A Noncooperative Solution for Coalition Formation and Payoff Negotiation
F
f-divergence inequalities	Bounds on the Privacy Amplification of Arbitrary Channels via the Contraction of $f_\alpha$-Divergence
Failure discovery	Failure Prediction from Limited Hardware Demonstrations
Fairness	Online Fair Allocation of Perishable Resources
farsightedness	A Noncooperative Solution for Coalition Formation and Payoff Negotiation
federated learning	Sketching for Distributed Deep Learning FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud The Role of Private Synthetic Data in Collaborative Learning
Federated learning (FL)	Bandit-Based Sequential Client Scheduling in Federated Learning
Federated LLM Fine-Tuning	A Modular Federated Suite for Low-Rank, Expressive, and Efficient LLM Fine-Tuning
Fine-tuning LLMs	Bridging Learning and Reasoning: From Solvers to LLMs
finite regime	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
flow-based models	FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
Focal loss	Focal Loss: Statistical and Information-Theoretic Perspectives
Follow-the-Perturbed-Leader	Follow-the-Perturbed-Leader with Between-Action Dependence
Follow-the-Regularized-Leader	Follow-the-Perturbed-Leader with Between-Action Dependence
formal methods	Is Neural Network Verification Useful and What Is Next?
formal verification	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS) Is Neural Network Verification Useful and What Is Next?
Foundation Models	Foundation Models for Spatio-temporal Physics
Function Approximation	New Convergence Rates for Function Approximation Using Kernel Methods Scalable and Convergent Algorithms for Strategically Risk-Averse Agents in Markov Games
G
game theory	Approximately Optimal Toll Design for Efficiency and Equity in Arc-Based Traffic Assignment Models Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling Deception against Game-Theoretic Learning in Complex Adaptive Systems
Gaussian Comparision Inequalities	A Precise Performance Analysis of the Randomized Singular Value Decomposition
generalized synchronization	On the role of time scale in reservoir computing
generative AI	Foundation Models for Spatio-temporal Physics Editing and inversion of images with flow models
Generative modeling	Measure Transport of Control Systems using Flow Matching
generative models	Automation and generative AI accelerated design of bio-therapeutics Distillation learns clean generative models from corrupted data A theoretical basis for model collapse in recursive training
Geometric Deep Learning	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator
ghost modulation	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
Good-Turing estimator	Estimating Error in Natural Distribution Estimation
Gossip Networks	Version Age of Information with Contact Mobility in Gossip Networks
graph neural network (GNN)	DPIR: Deep Predictive Interference-Aware Routing for Wireless Networks
Graph Neural Networks	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator
Graphon	The H-property for Asymmetric Graphons: The zero-one law
group formation	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
Group Testing	On Subset Retrieval and Group Testing Problems with Differential Privacy Constraints
groupcast	On Explicit Families of Outer Bounds for Broadcast Networks
Guidance problem	Differential Game Based Guidance with Delayed Engagement Decision
H
hamming coding	Regionally Robust Autoencoder-Based Channel Codes
Hardware Trojan	Z-Channel Modeling of Hardware Trojans The Pulse-Shaping Trojan: Refinements and New Results
Heavy-Tailed Noise	Reliable and Adaptive Stochastic Optimization in the Face of Messy Data
Heavy-traffic analysis	Join-the-Shortest-Queue with Markov-Modulated Parameters: Poisson Equation and Transform Techniques
heterogeneity	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
Heterogeneous stochastic systems	Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
hierarchical models	Hierarchical Implicit Neural Operators
high-dimensional data	Online Kernel CUSUM for Change-Point Detection
High-Probability Bounds	Reliable and Adaptive Stochastic Optimization in the Face of Messy Data
Human–AI collaboration	On Myopia in Rationally Inattentive Dynamic Information Acquisition
Hypothesis testing	Learning with Episodic Hypothesis Testing in General Games Distributed Hypothesis Testing and the Output Statistics of Random Binning Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach A Proof of The Changepoint Detection Threshold Conjecture in Preferential Attachment Models
hypothesis testing	An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources
I
I-MMSE	Path-Generalized I-MMSE: Bridging Diffusion and Autoregressive Generation Linking Diffusion Models & I-MMSE
identifiability	Ordinal-Poisson Causal Discovery
identification rate	An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources
image editing	Editing and inversion of images with flow models
Image restoration	DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP
impossibility upper bound	An Upper Bound for Interactive ECCs with Separate Budgets
Incentivization	Compression for Incentivization
Incomplete information	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
Infinite Dimensional Optimization	An Operator Theoretic Viewpoint of Reinforcement Learning and a class of PPO Algorithms
Influence Function	A FREQUENTIST THEORY FOR M-POSTERIORS: ASYMPTOTIC AND ROBUSTNESS PROPERTIES
information design	Persuasion under Dynamic Trust: Parametric Sender Behavior
information freshness	Distributed Caching of Transient Contents in a Tandem of Caches
Information Fusion	Towards a Nudge-Theoretic Cyber Deception Framework
Information Fusion	Optimal Sampling and Scheduling for Remote Fusion Estimation of Correlated Wiener Processes
Information structure	Principled Learning-to-Communicate with Quasi-Classical Information Structures
Information theoretic lower bounds	Diffusion bridges and adversarial examples
Information Theoretic Privacy	Private Counterfactual Retrieval
information theoretic security	Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation
Information Theory	Communication Systems with Mismatched Encoder and Decoders Focal Loss: Statistical and Information-Theoretic Perspectives
information theory	Towards a Unification of Logic and Information Theory
Information-Theoretic Privacy	Leaky Multi-Message Private Information Retrieval with Differential Privacy Guarantees
Integrated Sensing and Communication (ISAC)	On Estimation of Angles of Arrival in Monostatic ISAC Without Instantaneous Transmit CSI at the Transmiter
interactive error-correcting codes	An Upper Bound for Interactive ECCs with Separate Budgets
Interference Channel	Joint Constellation and Labeling Design for Gaussian Interference Channels via Autoencoders
Interference-powered networks	Minimum-Latency Reliable Routing in Interference-Powered Networks
interim stability	From signaling to interviews in random matching markets
Interpretable machine learning	Interpreting learned error-correcting codes
interval Markov decision process	Conservative Perception Models for Probabilistic Model Checking
Inverse Constraint Learning	Learning Neural Control Barrier Functions from Demonstrations
inverse problem	Provable Posterior Sampling with Score-Based Diffusion via Tilted Transport FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
inverse problems	Distillation learns clean generative models from corrupted data
J
Join the Shortest Queue	Join-the-Shortest-Queue with Markov-Modulated Parameters: Poisson Equation and Transform Techniques
joint communication and sensing	On Secrecy Capacity of Binary Beampointing Channels with Block Memory and Feedback
joint problems	Joint Problems in Learning Multiple Dynamical Systems
K
Kernel Methods	New Convergence Rates for Function Approximation Using Kernel Methods
kernel statistics	Online Kernel CUSUM for Change-Point Detection
knapsack problem	Sequential policies and the distribution of their total rewards in dynamic and stochastic knapsack problems
Koopman	When do practical Koopman embeddings exist?
Kron Reduction	Model Expansion to Realize Preferred Topologies
Kruskal's Algorithm	The Sum of Leaf Weights in the Minimum Spanning Tree of the Complete Graph
KV Cache	Tensor Product Attention Is All You Need
L
Language Models	Learning Without Forgetting
Large language model	On Speeding Up Language Model Evaluation
Large language models	Synchronizing Probabilities in Model-Driven Compression Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
Large language models (LLMs)	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
Large system analysis	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Latency	Minimum-Latency Reliable Routing in Interference-Powered Networks
Lattice	The Tarski Search Problem: Algorithms, Complexity, and Open Questions
LDPC	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
Learned error-correcting codes	Interpreting learned error-correcting codes
Learning in general games	Learning with Episodic Hypothesis Testing in General Games
learning linear dynamical systems	Joint Problems in Learning Multiple Dynamical Systems
Learning to communicate	Principled Learning-to-Communicate with Quasi-Classical Information Structures
Learning-enabled Autonomous Systems	Compositional Verification of Autonomous Systems
Learning-enabled Autonomy	StarV: A Qualitative and Quantitative Verification Framework for Learning-enabled Autonomy
Lifelong Learning	Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
limit theorems	Sequential policies and the distribution of their total rewards in dynamic and stochastic knapsack problems
Linear Control	Control of Dynamical Systems with Multiplicative Observation Noise with Unknown Distribution Parameters
linear quadratic regulator	A Reinforcement Learning View on the Sample Complexity of Linear Quadratic Regulator
linearization	When do practical Koopman embeddings exist?
Link function	Reinforcement Learning from Human Feedback with an Unknown Link Function
LLM	Challenges of Reliable Training and Evaluation of Large Language Models
LLM Fine-Tuning	A Modular Federated Suite for Low-Rank, Expressive, and Efficient LLM Fine-Tuning
load balancing	Monotone dynamics in network control
local differential privacy	Bounds on the Privacy Amplification of Arbitrary Channels via the Contraction of $f_\alpha$-Divergence
log-likelihood training	Linking Diffusion Models & I-MMSE
logic	Towards a Unification of Logic and Information Theory
Low-light	DarkDiff: Advancing Low-Light Raw Enhancement by Retasking Diffusion Models for Camera ISP
Lyapunov	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
Lyapunov Function	Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Lyapunov functions	A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
Lyapunov methods	Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
M
M-estimator	A FREQUENTIST THEORY FOR M-POSTERIORS: ASYMPTOTIC AND ROBUSTNESS PROPERTIES
M-MMSE	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
machine faults	Sequential Procedures for Early Detection of Machine Faults
machine learning	A Stochastic-Control Lense unifying Transformers, Diffusions & Reinforcement Learning HardNet: Hard-Constrained Neural Networks Problem-dependent convergence bounds for randomized linear gradient compression BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems
machine learning and learning theory	Reliable Inference at Scale Using Graph Structure
machine learning representations	Global Minimizers of Sigmoid Contrastive Loss
Majority-Logic Decoding	Maximal Achievable Service Rates of Codes and Connections to Combinatorial Designs
Majorization theory	On Myopia in Rationally Inattentive Dynamic Information Acquisition
Malliavin derivative	A Malliavin Calculus based Weak-Derivative Approach for Training Neural Stochastic Differential Equations
market power	Battery Operations in Electricity Markets: Strategic Behavior and Distortions
Markov chain	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
Markov Chain Monte Carlo	Stochastic model and decomposition schemes for relaxation oscillator based SAT solver
Markov chains	On Prophet Inequalities for Markov Rewards
Markov Decision Process	An Operator Theoretic Viewpoint of Reinforcement Learning and a class of PPO Algorithms
Markov Decision Process	Optimal Sampling and Scheduling for Remote Fusion Estimation of Correlated Wiener Processes
Markov Games	Scalable and Convergent Algorithms for Strategically Risk-Averse Agents in Markov Games
martingale convergence theorem	A theoretical basis for model collapse in recursive training
Massive MIMO	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Massive MIMO Radar	Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
Matrix factorization	On Speeding Up Language Model Evaluation
Matrix norms	On Myopia in Rationally Inattentive Dynamic Information Acquisition
Matrix Riccati Differential Equation	Artificial Parameter Based Approximate Solutions of Non-Symmetric Matrix Riccati Differential Equation
Mechanism Design	Compression for Incentivization
message-passing algorithm	From signaling to interviews in random matching markets
Microgrid network	Risk Sharing Among Microgrids: Connectivity Requirements and Optimal Control
millimeter-wave	On Secrecy Capacity of Binary Beampointing Channels with Block Memory and Feedback
Minimax optimality	Truncated LinUCB for Stochastic Linear Bandits
Minimum Spanning Tree	The Sum of Leaf Weights in the Minimum Spanning Tree of the Complete Graph
Minkowski sums	Asymptotic convexity of wide and shallow neural networks
missing mass	Learning and inference from temporally dependent data
Missing mass	Estimating Error in Natural Distribution Estimation
Mixing	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
MMSE	On Estimation of Angles of Arrival in Monostatic ISAC Without Instantaneous Transmit CSI at the Transmiter
model based RL	Reward Biasing in RL: Tempered Optimism for Exploration Improves Performance
model collapse	A theoretical basis for model collapse in recursive training
model reduction	Learning and predicting uncertain dynamical systems from data
Model Selection	Co-Optimization of Perception and Control for Autonomous Systems
model structural uncertainty	Learning and predicting uncertain dynamical systems from data
model-form error	Learning and predicting uncertain dynamical systems from data
monogamy-of-entanglement	Winning Rates of (n, k) Quantum Coset Monogamy Games
Monotone systems	Monotone dynamics in network control Reachable and Invariant Sets of Neural Controlled Systems via a Monotone Embedding
Monte Carlo methods	BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems
Multi armed bandit (MAB)	Bandit-Based Sequential Client Scheduling in Federated Learning
Multi-agent Reinforcement Learning	Scalable and Convergent Algorithms for Strategically Risk-Averse Agents in Markov Games
Multi-arm bandit	On Speeding Up Language Model Evaluation
multi-armed bandit	Optimal Change Detection in Multi-Armed Bandit
Multi-cell processing	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
multi-modal detection	Dual-Sensor Quickest Change Detection with Sampling Control
multi-party computation	Efficient and Privacy-Preserving Binary Dot Product via Multi-Party Computation
Multiple-Access Channel	Source-Channel Coding in Multiple-Access Channels with Correlated Sources
multiplex networks	Coordination Games on Multiplex Networks: Consensus and Convergence of Opinion Dynamics
Multiplicative Noise	Control of Dynamical Systems with Multiplicative Observation Noise with Unknown Distribution Parameters
Multitask learning	Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
multivariate time series	Cluster-Aware Causal Mixer for Sequential Change Detection in Multivariate Time Series
MVDR Beamforming	Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
N
net metering	Watts and Drops: Co-Scheduling Power and Water in Desalination Plants
network coding	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
Network constraints	Unit Commitment without Commitment: The Network Setting
network control	Monotone dynamics in network control
network flow	Optimal Battery Placement in Power Grid
network information theory	Distributed Hypothesis Testing and the Output Statistics of Random Binning
network topology	Optimal Battery Placement in Power Grid
Neural Control Barrier Functions	Learning Neural Control Barrier Functions from Demonstrations
neural differential equations	Learning and predicting uncertain dynamical systems from data
Neural Network Controllers	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS)
neural network verification	Generating and Checking DNN Verification Proofs Is Neural Network Verification Useful and What Is Next?
Neural Networks	HardNet: Hard-Constrained Neural Networks Reachable and Invariant Sets of Neural Controlled Systems via a Monotone Embedding BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems Compositional Verification of Autonomous Systems
Neural Operators	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator Hierarchical Implicit Neural Operators
neural perception	Conservative Perception Models for Probabilistic Model Checking
neural stochastic differential equation	A Malliavin Calculus based Weak-Derivative Approach for Training Neural Stochastic Differential Equations
Non-binary	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
non-equilibrium statistical physics	A Stochastic-Control Lense unifying Transformers, Diffusions & Reinforcement Learning
Non-monetary mechanism	Allocating Shared Resources via Dynamic Max-Min Fairness
noncooperative dynamic games	A Noncooperative Solution for Coalition Formation and Payoff Negotiation
Nonlinear control	Reachable and Invariant Sets of Neural Controlled Systems via a Monotone Embedding
nonlinear dynamic system	FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
nonlinear dynamics	On the role of time scale in reservoir computing
Nonlinear Systems	Measure Transport of Control Systems using Flow Matching
Nudges	Towards a Nudge-Theoretic Cyber Deception Framework
numerical analysis	Hierarchical Implicit Neural Operators
O
Oblivious Transfer	Single-Server SPIR over Binary Erasure Channels: Benefits of Noisy Side Information
offline reinforcement learning	A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
online algorithm	Sequential policies and the distribution of their total rewards in dynamic and stochastic knapsack problems
Online algorithms	Online Bipartite Matching with Advice
online allocation	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
Online convex optimization	Error-Sensitive Dynamic Calibration for Online Optimization with Switching Costs
Online Learning	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement Follow-the-Perturbed-Leader with Between-Action Dependence
Online Linear Optimization	Follow-the-Perturbed-Leader with Between-Action Dependence
Online matching	Online Bipartite Matching with Advice
Online Resource Allocation	Online Fair Allocation of Perishable Resources Target-Following Online Resource Allocation Using Proxy Assignments
opacity	System Opacity Formulations and Applications to Privacy Preservation in Smart Grids
Open questions	The Tarski Search Problem: Algorithms, Complexity, and Open Questions
Operating Envelopes	Inexactness of Second-order Cone Relaxations for Calculating Operating Envelopes
Opinion dynamics	Coordination Games on Multiplex Networks: Consensus and Convergence of Opinion Dynamics
optimal battery placement	Optimal Battery Placement in Power Grid
Optimal Control	Risk Sharing Among Microgrids: Connectivity Requirements and Optimal Control
optimal experimental design	Learning and predicting uncertain dynamical systems from data
optimal experimental design (OED)	Confronting Uncertainty in AI for Science
Optimal stopping	On Prophet Inequalities for Markov Rewards
Optimal Transport	A time-reversal methodology for steering the state of control-affine stochastic systems
Optimization	Sketching for Distributed Deep Learning HardNet: Hard-Constrained Neural Networks Optimizing Age of Information without Knowing the Age of Information Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
Optimization	Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals
optimization performance analysis	Reliable Inference at Scale Using Graph Structure
Optimization Theory	Approximately Optimal Toll Design for Efficiency and Equity in Arc-Based Traffic Assignment Models
Outage constrained routing	Minimum-Latency Reliable Routing in Interference-Powered Networks
outliers	Optimal Bounded-Influence Procedure for Robust Sequential Change-Point Detection
P
P-MMSE	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Partial Information	Linear-Quadratic Stackelberg Differential Games for Jump-Diffusion Systems with Complete and Partial Information
PDE	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator
Perception models	Co-Optimization of Perception and Control for Autonomous Systems
Perishability	Online Fair Allocation of Perishable Resources
perturbation	Regionally Robust Autoencoder-Based Channel Codes
Pessimism Principle	Pessimism for Zero-Shot Transfer in RL
physical intelligence	Active Generative Models for Inference and Learning in Complex Physical World
Physical-Layer Security	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
Pilot contamination	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Poincare	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
Poisson equation	Join-the-Shortest-Queue with Markov-Modulated Parameters: Poisson Equation and Transform Techniques
Poisson functional representation	Exact Channel Simulation under Exponential Cost
polyhedral cone	Towards an optimal solution to NMF
post-allocation service	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
posterior sampling	Provable Posterior Sampling with Score-Based Diffusion via Tilted Transport
POVM optimization	Quickest Quantum Change Point Detection
Power electronic converters	Optimal Setpoints of Current Constrained Converters-Based Resources
Power Flow	Model Expansion to Realize Preferred Topologies
Power Modulation	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
Power system operations	Optimal Setpoints of Current Constrained Converters-Based Resources
Power Systems	Model Expansion to Realize Preferred Topologies
Pre-order preserving linear maps	Compression for Incentivization
Preferential attachment models	A Proof of The Changepoint Detection Threshold Conjecture in Preferential Attachment Models
Preventive and reactive defense	Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals
Price optimization	Experimentation in the Presence of Strategic Buyers: Unbiased Estimation Under Intertemporal Substitution
pricing	Pricing in Discrete Markets Using Copositive Duality Optimal Mechanisms for Demand Response: An Indifference Set Approach
privacy amplification	Bounds on the Privacy Amplification of Arbitrary Channels via the Contraction of $f_\alpha$-Divergence
privacy costs	Optimal Data Acquisition with Privacy-Aware Agents
privacy preservation	System Opacity Formulations and Applications to Privacy Preservation in Smart Grids
private information retrieval	On Subset Retrieval and Group Testing Problems with Differential Privacy Constraints Improved Achievable Rate for Single Server SPIR over BEC
Private Information Retrieval	Leaky Multi-Message Private Information Retrieval with Differential Privacy Guarantees
Probabilistic Minimum Spanning Tree Problem	The Sum of Leaf Weights in the Minimum Spanning Tree of the Complete Graph
probabilistic model checking	Conservative Perception Models for Probabilistic Model Checking
proof certification	Generating and Checking DNN Verification Proofs
proof generation and checking	Generating and Checking DNN Verification Proofs
Prophet inequalities	On Prophet Inequalities for Markov Rewards
protein design	Automation and generative AI accelerated design of bio-therapeutics
proxy assignments	Target-Following Online Resource Allocation Using Proxy Assignments
Pulse Shaping filter	The Pulse-Shaping Trojan: Refinements and New Results
Pushing the Efficiency-Performance Trade-Off	A Modular Federated Suite for Low-Rank, Expressive, and Efficient LLM Fine-Tuning
Q
quality constraint	Dual-Sensor Quickest Change Detection with Sampling Control
Quantile regression	A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
quantum algorithms	A Cutting-plane Method for Semidefinite Programming with Potential Applications on Noisy Quantum Devices
Quantum capacity	Relaying Quantum Information
quantum correlations	Winning Rates of (n, k) Quantum Coset Monogamy Games
quantum games	Winning Rates of (n, k) Quantum Coset Monogamy Games
Quantum relay channels	Relaying Quantum Information
Quantum repeaters	Relaying Quantum Information
Quasi cyclic	Reduced Complexity Encoding of Non-binary Quasi Cyclic Low-Density Parity-Check Codes
queue	Mixing Times for Reversible Countable State Markov Chains: A case study of the Erlang-C queue
Queueing systems	Scheduling with Uncertain Holding Costs and its Application to Content Moderation
Queueing theory	If the Virus Respected Queues
quickest change detection	Sequential Procedures for Early Detection of Machine Faults Dual-Sensor Quickest Change Detection with Sampling Control Sequential Change Point Detection via Denoising Score Matching
quickest detection	Optimal Change Detection in Multi-Armed Bandit Optimal Bounded-Influence Procedure for Robust Sequential Change-Point Detection
quickest quantum channel change detection	Quickest Quantum Change Point Detection
quickest quantum state change detection	Quickest Quantum Change Point Detection
R
random binning	Distributed Hypothesis Testing and the Output Statistics of Random Binning
random graph	The H-property for Asymmetric Graphons: The zero-one law
Random Graphs	The Sum of Leaf Weights in the Minimum Spanning Tree of the Complete Graph
random matching markets	From signaling to interviews in random matching markets
random matrices	Problem-dependent convergence bounds for randomized linear gradient compression
Random matrix theory	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Randomized algorithm	Stochastic model and decomposition schemes for relaxation oscillator based SAT solver
randomized cutting-plane method	A Cutting-plane Method for Semidefinite Programming with Potential Applications on Noisy Quantum Devices
Randomized Singular Value Decomposition	A Precise Performance Analysis of the Randomized Singular Value Decomposition
Randomized SVD	A Precise Performance Analysis of the Randomized Singular Value Decomposition
rate region	An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources
Rate-Distortion Theory	Zero Perception Error Rate-Distortion for Semantic Communication
rate-distortion-perception	Rate-Distortion-Perception Trade-off in Summarization
Rational Inattention	On Myopia in Rationally Inattentive Dynamic Information Acquisition
Reachability Analysis	StarV: A Qualitative and Quantitative Verification Framework for Learning-enabled Autonomy
real-time	Battery Operations in Electricity Markets: Strategic Behavior and Distortions
reasoning	Towards a Unification of Logic and Information Theory
reasoning	Challenges of Reliable Training and Evaluation of Large Language Models
reasoning models	Automation and generative AI accelerated design of bio-therapeutics
Reconfigurable Antenna Arrays	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
rectified flow	Editing and inversion of images with flow models
recursive training	A theoretical basis for model collapse in recursive training
refugee matching	Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
Regression	Soft Training: Method for Neural Network Learning
regret	Sequential policies and the distribution of their total rewards in dynamic and stochastic knapsack problems
Reinforcement Learning	Reinforcement Learning Design for Quickest Change Detection - Extended Abstract Reward Biasing in RL: Tempered Optimism for Exploration Improves Performance An Operator Theoretic Viewpoint of Reinforcement Learning and a class of PPO Algorithms Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
reinforcement learning	A Reinforcement Learning View on the Sample Complexity of Linear Quadratic Regulator
Reinforcement Learning from Human Feedback (RLHF)	Reinforcement Learning from Human Feedback with an Unknown Link Function
Reinforcement Learning with Symbolic Feedback	Bridging Learning and Reasoning: From Solvers to LLMs
Relay-Channel	Information-Theoretic Outer-bounds from Sphere-Packing, Compactness, and Zero-One Laws
Reliability	Minimum-Latency Reliable Routing in Interference-Powered Networks
reliability security and trust	Reliable Inference at Scale Using Graph Structure
Remote Estimation	Optimal Sampling and Scheduling for Remote Fusion Estimation of Correlated Wiener Processes
renewable energy	Watts and Drops: Co-Scheduling Power and Water in Desalination Plants
reoptimization	Sequential policies and the distribution of their total rewards in dynamic and stochastic knapsack problems
representation alignment	Global Minimizers of Sigmoid Contrastive Loss
Representation Learning	Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
Reproducing Kernel Hilbert Space	New Convergence Rates for Function Approximation Using Kernel Methods
reservoir computing	On the role of time scale in reservoir computing
Resource allocation	Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals
resource pooling	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
Restless Bandits	Scheduling with Uncertain Holding Costs and its Application to Content Moderation
restless multi armed bandits	Distributed Caching of Transient Contents in a Tandem of Caches
Ridge regression	On the Sign Structure of the Ridge Estimator for Nonnegative Linear Mappings
Risk-seeking Policy Optimization	Analytical Lyapunov Function Discovery: An RL-based Generative Approach
RLHF	Challenges of Reliable Training and Evaluation of Large Language Models
Robust MDP	Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
Robust regression	A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
robust reinforcement learning	A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
robustness	Regionally Robust Autoencoder-Based Channel Codes A FREQUENTIST THEORY FOR M-POSTERIORS: ASYMPTOTIC AND ROBUSTNESS PROPERTIES
Robustness quantification	Optimal Bounded-Influence Procedure for Robust Sequential Change-Point Detection
rolling element bearing	Sequential Procedures for Early Detection of Machine Faults
ROPE	Tensor Product Attention Is All You Need
routing algorithms	DPIR: Deep Predictive Interference-Aware Routing for Wireless Networks
RSVD	A Precise Performance Analysis of the Randomized Singular Value Decomposition
Rényi divergence	Exact Channel Simulation under Exponential Cost
Rényi entropy	Exact Channel Simulation under Exponential Cost
Rényi-divergence	Bounds on the Privacy Amplification of Arbitrary Channels via the Contraction of $f_\alpha$-Divergence
S
Safe Autonomous Systems	Co-Optimization of Perception and Control for Autonomous Systems
Safety	HardNet: Hard-Constrained Neural Networks
Sample complexity	A Reinforcement Learning View on the Sample Complexity of Linear Quadratic Regulator Principled Learning-to-Communicate with Quasi-Classical Information Structures
Sampling	Measure Transport of Control Systems using Flow Matching
sampling control	Dual-Sensor Quickest Change Detection with Sampling Control Optimal Change Detection in Multi-Armed Bandit
SAT/SMT Solvers	Bridging Learning and Reasoning: From Solvers to LLMs
Scalability	Abstractions for Scalable Analysis of AI-enabled Cyber-Physical Systems (CPS)
Scalable pilot assignment	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Scheduling	Optimizing Age of Information without Knowing the Age of Information Bandit-Based Sequential Client Scheduling in Federated Learning Scheduling with Uncertain Holding Costs and its Application to Content Moderation
Scheduling Algorithm	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
score-based diffusion	Provable Posterior Sampling with Score-Based Diffusion via Tilted Transport
Second-order Cone Power Flow Relaxation	Inexactness of Second-order Cone Relaxations for Calculating Operating Envelopes
Secrecy	Near-Field Quiet Zone Using Passive XL-RIS for 6G-IoT Coexistence in the Upper Mid-Band
secrecy capacity	On Secrecy Capacity of Binary Beampointing Channels with Block Memory and Feedback
security	Deception against Game-Theoretic Learning in Complex Adaptive Systems
self-driving laboratory	Automation and generative AI accelerated design of bio-therapeutics
Semantic Communication	Zero Perception Error Rate-Distortion for Semantic Communication Communication Systems with Mismatched Encoder and Decoders
semantic communications	Rate-Distortion-Perception Trade-off in Summarization
semantics	Towards a Unification of Logic and Information Theory
semidefinite programming	A Cutting-plane Method for Semidefinite Programming with Potential Applications on Noisy Quantum Devices
sequential change detection	Cluster-Aware Causal Mixer for Sequential Change Detection in Multivariate Time Series
Sequential decision making	Bandit-Based Sequential Client Scheduling in Federated Learning
Sequential decision-making	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
Sequential decision-making	Towards a Nudge-Theoretic Cyber Deception Framework
sequential detection	Sequential Procedures for Early Detection of Machine Faults
sequential test	Optimal Change Detection in Multi-Armed Bandit
Series expansion	Artificial Parameter Based Approximate Solutions of Non-Symmetric Matrix Riccati Differential Equation
Service rate regions	Maximal Achievable Service Rates of Codes and Connections to Combinatorial Designs
SGD	A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
shallow and wide networks	Asymptotic convexity of wide and shallow neural networks
Shared resource allocation	Allocating Shared Resources via Dynamic Max-Min Fairness
side channels	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
Side information	Single-Server SPIR over Binary Erasure Channels: Benefits of Noisy Side Information
Sign structure analysis	On the Sign Structure of the Ridge Estimator for Nonnegative Linear Mappings
signaling mechanism	From signaling to interviews in random matching markets
sketching	Sketching for Distributed Deep Learning
smart grid	System Opacity Formulations and Applications to Privacy Preservation in Smart Grids
Soft-decision decoding	Soft Training: Method for Neural Network Learning
source coding	Distributed Hypothesis Testing and the Output Statistics of Random Binning
source signal separation	Hybrid Atomic Norm Sparse/Diffuse Channel Estimation
Source-Channel Coding	Source-Channel Coding in Multiple-Access Channels with Correlated Sources
spatial cohesion	Group Formation through Game Theory and Agent-Based Modeling: Spatial Cohesion, Heterogeneity, and Resource Pooling
Spatially correlated Rayleigh fading	Multi-Cell MMSE Processing and Pilot Assignment in Massive MIMO under Correlated Fading
Sphere-packing	Information-Theoretic Outer-bounds from Sphere-Packing, Compactness, and Zero-One Laws
SPIR	Improved Achievable Rate for Single Server SPIR over BEC Single-Server SPIR over Binary Erasure Channels: Benefits of Noisy Side Information
Spot Instances	FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
Stability	Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Stackelberg games	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
Stackelberg Games	Linear-Quadratic Stackelberg Differential Games for Jump-Diffusion Systems with Complete and Partial Information
State space collapse	Join-the-Shortest-Queue with Markov-Modulated Parameters: Poisson Equation and Transform Techniques
Statistical analysis	BayesFlow++: A Unified Framework for Amortized Bayesian Inference in Complex Systems
Stochastic Control	Reinforcement Learning Design for Quickest Change Detection - Extended Abstract A time-reversal methodology for steering the state of control-affine stochastic systems Control of Dynamical Systems with Multiplicative Observation Noise with Unknown Distribution Parameters
stochastic gradient algorithm	A Malliavin Calculus based Weak-Derivative Approach for Training Neural Stochastic Differential Equations
stochastic gradient descent	Asymptotic convexity of wide and shallow neural networks
Stochastic Hybrid Systems	Version Age of Information with Contact Mobility in Gossip Networks
Stochastic linear bandits	Truncated LinUCB for Stochastic Linear Bandits
stochastic localization	Path-Generalized I-MMSE: Bridging Diffusion and Autoregressive Generation
Stochastic Maximum Principle	Linear-Quadratic Stackelberg Differential Games for Jump-Diffusion Systems with Complete and Partial Information
stochastic optimal control	A Stochastic-Control Lense unifying Transformers, Diffusions & Reinforcement Learning
Stochastic Optimization	Reliable and Adaptive Stochastic Optimization in the Face of Messy Data
stochastic optimization	Problem-dependent convergence bounds for randomized linear gradient compression
Stochastic Processes	Risk Sharing Among Microgrids: Connectivity Requirements and Optimal Control If the Virus Respected Queues
stopping time	Optimal Change Detection in Multi-Armed Bandit
Storage vs Transport Capacity Tradeoffs	Risk Sharing Among Microgrids: Connectivity Requirements and Optimal Control
strategic communication	Persuasion under Dynamic Trust: Parametric Sender Behavior
Strategic deception	LLM-Stackelberg Games: Conjectural Reasoning Equilibria, Meta-Cognition, and Applications to Spearphishing
strong data processing inequalities	Bounds on the Privacy Amplification of Arbitrary Channels via the Contraction of $f_\alpha$-Divergence
strong duality	Pricing in Discrete Markets Using Copositive Duality
strong Nash equilibrium	A Noncooperative Solution for Coalition Formation and Payoff Negotiation
structural system theory	The H-property for Asymmetric Graphons: The zero-one law
Sub-quadratic	A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
subspace	Towards an optimal solution to NMF
subspace permutations	Winning Rates of (n, k) Quantum Coset Monogamy Games
subspace states	Winning Rates of (n, k) Quantum Coset Monogamy Games
switch-type policies	Optimal Service Mode Assignment in a Simple Computation Offloading System
Switchback experiments	Experimentation in the Presence of Strategic Buyers: Unbiased Estimation Under Intertemporal Substitution
Symbolic reasoning	Bridging Learning and Reasoning: From Solvers to LLMs
Symbolic Transformer	Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Symmetric Private Information Retrieval	Improved Achievable Rate for Single Server SPIR over BEC Single-Server SPIR over Binary Erasure Channels: Benefits of Noisy Side Information
synthetic data	The Role of Private Synthetic Data in Collaborative Learning
synthetic data augmentation	Learning and predicting uncertain dynamical systems from data
System Identification	Learning and predicting uncertain dynamical systems from data Control of Dynamical Systems with Multiplicative Observation Noise with Unknown Distribution Parameters
T
Target Detection	Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
target following	Target-Following Online Resource Allocation Using Proxy Assignments
Tarski’s theorem	The Tarski Search Problem: Algorithms, Complexity, and Open Questions
Tensor Product Attention	Tensor Product Attention Is All You Need
test-time scaling	Challenges of Reliable Training and Evaluation of Large Language Models
Testing	Failure Prediction from Limited Hardware Demonstrations
text summarization	Rate-Distortion-Perception Trade-off in Summarization
Thompson Sampling	Follow-the-Perturbed-Leader with Between-Action Dependence
time series forecasting	On the role of time scale in reservoir computing
Time-reversal	A time-reversal methodology for steering the state of control-affine stochastic systems
time-varying constraints	Target-Following Online Resource Allocation Using Proxy Assignments
timing synchronization	Side Channel Communications With Ghost Modulation Over the Asymmetric Binary Crossover Erasure Channel
Traffic control	Approximately Optimal Toll Design for Efficiency and Equity in Arc-Based Traffic Assignment Models
training dynamics	Transformers Provably Learn Symbolic Multi-step Reasoning via Chain of Thought
Transfer Reinforcement Learning	Pessimism for Zero-Shot Transfer in RL
Transformers	Transformers Provably Learn Symbolic Multi-step Reasoning via Chain of Thought
Transport	Measure Transport of Control Systems using Flow Matching
Trojan Detectability	Z-Channel Modeling of Hardware Trojans
truncated epigraphs	Asymptotic convexity of wide and shallow neural networks
trust	Persuasion under Dynamic Trust: Parametric Sender Behavior
U
uncertain max flow	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
uncertain min cut	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
Uncertainty Quantification	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator Learning and inference from temporally dependent data
uncertainty quantification (UQ)	Confronting Uncertainty in AI for Science
unified approach	A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
unit commitment	Pricing in Discrete Markets Using Copositive Duality
Unit commitment	Unit Commitment without Commitment: The Network Setting
universal adversarial attack	Regionally Robust Autoencoder-Based Channel Codes
universal information theory	Active Generative Models for Inference and Learning in Complex Physical World
Unknown Distribution	Control of Dynamical Systems with Multiplicative Observation Noise with Unknown Distribution Parameters
Upper confidence bounds	Truncated LinUCB for Stochastic Linear Bandits
User preferences and Actionability	Private Counterfactual Retrieval
V
value of data	Toward a Theory of Data Ecology: Understanding and Steering Data Ecosystems
variable max flow	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
variable maximum flow	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
variable min cut	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
variable minimum cut	Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
Variable-length codes	Exact Channel Simulation under Exponential Cost
Variational Inference	Probabilistic DiffusionNet: A geometry informed probabilistic neural operator
W
water-energy nexus	Watts and Drops: Co-Scheduling Power and Water in Desalination Plants
Watermarking	Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
weak derivative estimator	A Malliavin Calculus based Weak-Derivative Approach for Training Neural Stochastic Differential Equations
Weakly coupled stochastic dynamic programs	Unit Commitment without Commitment: The Network Setting
Weakly-coupled MDPs	Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
Wiener filter	On the Sign Structure of the Ridge Estimator for Nonnegative Linear Mappings
Wireless Communication	The Pulse-Shaping Trojan: Refinements and New Results
Wireless networks	Optimizing Age of Information without Knowing the Age of Information DPIR: Deep Predictive Interference-Aware Routing for Wireless Networks
world models	Active Generative Models for Inference and Learning in Complex Physical World
Z
Z Channel	Z-Channel Modeling of Hardware Trojans
Zero Perception Error	Zero Perception Error Rate-Distortion for Semantic Communication
zero-one law	The H-property for Asymmetric Graphons: The zero-one law
Zero-One Laws	Information-Theoretic Outer-bounds from Sphere-Packing, Compactness, and Zero-One Laws
Zero-Shot Learning	Pessimism for Zero-Shot Transfer in RL
zeroth-order optimization	Reinforcement Learning from Human Feedback with an Unknown Link Function

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