2024 ALLERTON: 60TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING

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

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$\alpha$-lift	Privacy-Utility Tradeoff Based on $\alpha$-lift
$\varepsilon\textrm{-}$ differential privacy	Chernoff Information as a Privacy Constraint for Adversarial Classification
6
6G	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
A
AC/DC grid	Information Structures in AC/DC Grids
achievability bounds	Finite-Length Coding Bounds via Guesswork
Acknowledgement Feedback	Acknowledgment Feedback in Directed Graphs via Deterministic and Probabilistic Strategies
Active Exploration	Active Exploration for Minimax Estimation in MDPs
Actor- critic method	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
Adaptive experimentation	Post-Contextual Bandit Inference with Adaptive Stopping
adaptive stepsize	Toward Parameter-free Decentralized Optimization
Admittance matrix estimation	Reverse Kron Reduction on Trees
adversarial classification	Chernoff Information as a Privacy Constraint for Adversarial Classification
adversarial label noise	Robustly Learning Single-Index Models via Alignment Sharpness
Age of Gossip	Mobility in Age-Based Gossip Networks
Agent Model	From Large Language Models to Large Agent Models: Planning and Reasoning with Physical World Knowledge
agnostic learning	Robustly Learning Single-Index Models via Alignment Sharpness
AI Safety	Mitigating Backdoor Threats to Large Language Models
Alignment	Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Anomaly detection	Active Change Point Anomaly Detection Over Composite Hypotheses
APPR	On the scalability of large graph methods for kernel-based machine learnin
approximate message passing	OpAMP: Linear Regressions with Erasures
arbitrarily varying multiple-access channel	Authenticated partial correction over AV-MACs: toward characterization and coding
Asymmetric and Symmetric Hypothesis Testing	Acceptance in Postselected Asymptotic Quantum State Discrimination
Asymptotic bias	Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation
asymptotic statistics	Quickest Change Detection Using Mismatched CUSUM
authentication	Authenticated partial correction over AV-MACs: toward characterization and coding
average-case optimization	Sharply predicting optimization trajectories in high-dimensions: State evolutions beyond first-order algorithms
AWGN Channel	Capacity of a Complex-Valued Gaussian Channel with Frequency Offset
AWGN channel with feedback	Higher-order Interpretations of Deepcode, a Learned Feedback Code
B
B-SAT	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
Backdoor Threats	Mitigating Backdoor Threats to Large Language Models
Balanced truncation model order reduction	Scalable computations for nonlinear balanced truncation model reduction
Bandits	Sequential Design of Experiments in Causal Systems
Barrier function	Generalized Barrier Functions: Integral Conditions & Recurrent Relaxations
Bayesian estimation	Characterization of Slow Convergence in Word-of-Mouth Social Learning
Bayesian game	Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network
belief-propagation decoding	Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation
Best of both worlds	Instance-Optimality in Online Learning
biclustering	Metric Clustering From Triplet Comparisons
bicycle codes	Quantum Margulis Codes
Binary images	Lossless Binary Image Compression Using Learned Multi-level Dictionaries
Boolean satisfiability problem	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
Brunn-Minkowski theory	Optimal Regularization for a Data Source
C
Caching	Caching or Pre-fetching? The Role of Hazard Rates
capacity	Differential Privacy in the Large Composition Regime
capacity region	Authenticated partial correction over AV-MACs: toward characterization and coding
Carrier Frequency Offset	Capacity of a Complex-Valued Gaussian Channel with Frequency Offset
Cascade connection	On topological entropy of switched cascade systems
causality	Sequential Design of Experiments in Causal Systems
CCPA	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation
censorship	Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network
change detection	Quickest Change Detection Using Mismatched CUSUM
Change-point detection	Active Change Point Anomaly Detection Over Composite Hypotheses Higher-criticism for multi-sensor sparse change-point detection
channel capacity	Capacity of a Complex-Valued Gaussian Channel with Frequency Offset An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
channel simulation	Optimal Redundancy in Exact Channel Synthesis
channel synthesis	Optimal Redundancy in Exact Channel Synthesis
Channels with memory	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
characteristic graph entropy	Multi-Functional Distributed Computing
Chernoff information	Chernoff Information as a Privacy Constraint for Adversarial Classification
Circuit Synthesis	New methods for quantum circuit synthesis with symmetry-respecting gates
Classification	Classification with a Network of Partially Informative Agents: Enabling Wise Crowds from Individually Myopic Classifiers
closed box testing	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
clustering	Metric Clustering From Triplet Comparisons
Coding Theorem	Capacity of a Complex-Valued Gaussian Channel with Frequency Offset
Coding Theory	Restricted Converse Results for g-Group Complete-{s} Pliable Index Coding Problems
communication	Understanding Neural Population Communication with Latent Channels
Communication Complexity	The Sample-Communication Complexity Trade-off in Federated Q-Learning
communication efficiency	Temporal Predictive Coding for Gradient Compression in Distributed Learning
communication-efficiency	Communication-Efficient Federated Learning via Sparse Training with Regularized Error Correction
communication-efficient	Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
competitive ratio	collaborative exploration of unknown environments
composition	Chernoff Information as a Privacy Constraint for Adversarial Classification Optimized Mechanisms for Differentially Private Composition
Compound Channel	Capacity of a Complex-Valued Gaussian Channel with Frequency Offset
compound matrices	A sufficient condition for 2-contraction of a feedback interconnection
Computational limits	Sharp information-theoretic thresholds for shuffled linear regression
confidence sequences	Power-one sequential tests, confidence sequences, e-processes and e-detectors
conjunctive normal form (CNF)	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
Constrained optimization	Structured Regularization for SPD Optimization with Side Information Stochastic-Gradient-based Interior-Point Methods
Contextual bandits	Post-Contextual Bandit Inference with Adaptive Stopping
Continuous optimization	Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion Stochastic-Gradient-based Interior-Point Methods
contraction coefficient	Contraction Coefficients of Product Symmetric Channels
Contraction theory	A sufficient condition for 2-contraction of a feedback interconnection Reachability Analysis of Dynamical Systems: A Mixed Monotone Contracting Approach
Control emulation	Minimum Data-Rate for Emulating a Linear Feedback System
Control under communication constraints	Minimum Data-Rate for Emulating a Linear Feedback System
Controllability and Observability	Scalable computations for nonlinear balanced truncation model reduction
Controlled sensing	Active Change Point Anomaly Detection Over Composite Hypotheses
convergence analysis	How Do System Dynamics Affect the Convergence of Federated Learning?
converse bounds	Finite-Length Coding Bounds via Guesswork
convex bodies	Optimal Regularization for a Data Source
Coordination	On the role of network structure in learning to coordinate with bounded rationality
Correlated equilibrium	Constrained Correlated Equilibria
correlation	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation
Coupled Constraints	Constrained Correlated Equilibria
coupled power-transportation systems	Braess’ Paradoxes in Electrified Transportation
CSS codes	GNarsil: Splitting Stabilizers into Gauges
CSS-T code	Binary Triorthogonal and CSS-T Codes for Quantum Error Correction
CVaR	Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
Cyber Deception	A Hypothesis Testing-based Framework for Cyber Deception with Sludging
Cyber-attack Detection	Transferable Learning of GCN Sampling Graph Data Clusters from Different Power Systems
D
data correlations	Multi-Functional Distributed Computing
Data Privacy	Distributed Matrix Multiplication: Download Rate, Randomness and Privacy Trade-Offs
Data-driven model predictive control	Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
Decentralized control	Information Structures in AC/DC Grids Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Decentralized Learning	Communication-efficient and Decentralized Federated Minimax Optimization
Decentralized multiagent systems	Incentive Analysis for Agent Participation in Federated Learning
Decentralized optimization	Toward Parameter-free Decentralized Optimization Decentralized Equitable Energy Access in Energy Communities
Decision-making	Do LLM Agents Have Regret? A Case Study in Online Learning and Games
deep learning	Communication-Efficient Federated Learning via Sparse Training with Regularized Error Correction A robust testing approach to measuring model varability
deep-learned error-correcting codes	Higher-order Interpretations of Deepcode, a Learned Feedback Code
Delays	Acknowledgment Feedback in Directed Graphs via Deterministic and Probabilistic Strategies
Design-based inference	Post-Contextual Bandit Inference with Adaptive Stopping
Detection
Dictionary learning	Lossless Binary Image Compression Using Learned Multi-level Dictionaries
Dictionary-based compression	Lossless Binary Image Compression Using Learned Multi-level Dictionaries
Difference of Convex optimization	Structured Regularization for SPD Optimization with Side Information
Difference-of-convex functions	Distributed Difference of Convex Optimization
Difference-of-convex programming	Distributed Difference of Convex Optimization
differential inclusion	Lyapunov-like converse result for strong forward invariance
differential privacy	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation Differential Privacy and Sublinear Time are Incompatible Sometimes Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning Differentially Private Space-Efficient Algorithms for Frequency Moment Estimation in the Turnstile Model Differentially Private Sinkhorn Algorithm Differentially Private Graph Diffusion with Applications in Personalized PageRanks Optimized Mechanisms for Differentially Private Composition Differential Privacy in the Large Composition Regime Private Online Community Detection for Censored Block Models Training Language Models on Private Federated Data in the Age of LLMs
diffusion models	Stochastic interpolants: A unifying framework for flows and diffusions On solving inverse problems in computer vision using latent diffusion models
Digital storage	Graph Codes for Dual-Parameter Barrier Channels
dimension reduction	Understanding Neural Population Communication with Latent Channels
Directed graphs	Distributed Difference of Convex Optimization
Directed topologies	Acknowledgment Feedback in Directed Graphs via Deterministic and Probabilistic Strategies
distance learning	Metric Clustering From Triplet Comparisons
Distributed Average Consensus	Acknowledgment Feedback in Directed Graphs via Deterministic and Probabilistic Strategies
Distributed computation	Multi-Functional Distributed Computing
Distributed Computing	The Power Method with Row Erasures Distributed Matrix Multiplication: Download Rate, Randomness and Privacy Trade-Offs
Distributed control	Stability-Constrained Voltage Control in Distribution Grids
Distributed energy resources	Stability-Constrained Voltage Control in Distribution Grids Fair-Over-Time Distributed Energy Resource Coordination Hierarchical Control of Distribution Grids with Application to Transmission-Distribution Fast Frequency Control
distributed fact-checking	Influence Chain Recovery and Application in Distributed Fact-Checking
Distributed gradient algorithm
Distributed gradient descent	Distributed Difference of Convex Optimization
Distributed learning	Temporal Predictive Coding for Gradient Compression in Distributed Learning
Distributed optimization	Distributed Difference of Convex Optimization Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
distributionally robust models	Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
Distributionally robust optimization	Distributionally Robust Optimal Transport for Improved Model Robustness Achieving the Asymptotically Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach
diverse preferences	Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Domain adaptation	Distributionally Robust Optimal Transport for Improved Model Robustness
Drift Method	Transform Method for Markov-Modulated Queues
Duality	Closing the Duality Gap on Integer Linear Programming Robust Distribution Estimation via Partial Optimal Transport
Dynamic Games	Tractable Equilibrium Computation in Markov Games through Risk Aversion
dynamic programming	Solving Markov Decision Processes via Reward Balancing
Dynamic Stability	Exploring Feasible Transition from Local to Global Optima in Power Systems
dynamical transport of measure	Stochastic interpolants: A unifying framework for flows and diffusions
E
e-detector	Power-one sequential tests, confidence sequences, e-processes and e-detectors
Efficiency	Efficient LLM Serving via Lossy Computation
Electricity markets	Balancing Fairness and Efficiency in Power Systems with Large and Small Users
electronic design automation(EDA)	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
Energy communities	Decentralized Equitable Energy Access in Energy Communities
ensemble models	A robust testing approach to measuring model varability
entanglement	Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction
Entropic regularization	Differentially Private Sinkhorn Algorithm
Entropy	Remote robust state estimation problem
Entropy regularization	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
equity	Fair-Over-Time Distributed Energy Resource Coordination
Equity and efficiency tradeoff	Decentralized Equitable Energy Access in Energy Communities
equivalent-circuit modeling	Equivalent-circuit Modeling Framework to Facilitate Large-signal Stability Assessment of Inverter-based Resources
Equivalent-circuit models	Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions
erasure tolerance	The Power Method with Row Erasures
Error correction codes	Graph Codes for Dual-Parameter Barrier Channels
estimation	Robust Distribution Estimation via Partial Optimal Transport
event-triggered communication	Temporal Predictive Coding for Gradient Compression in Distributed Learning
exact trajectory predictions	Sharply predicting optimization trajectories in high-dimensions: State evolutions beyond first-order algorithms
F
fairness	Balancing Fairness and Efficiency in Power Systems with Large and Small Users Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
fault analysis	Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions
fault tolerance	Binary Triorthogonal and CSS-T Codes for Quantum Error Correction
Feature Extraction	Beyond PCA: A Gram-Schmidt Approach to Feature Extraction
Federated learning	A Masked Pruning-Based Algorithm for Dimensionality Reduction in Federated Learning Systems Personalized Federated Learning with Shared Linear Representation: Statistically Optimal Rates Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method The Sample-Communication Complexity Trade-off in Federated Q-Learning Training Language Models on Private Federated Data in the Age of LLMs How Do System Dynamics Affect the Convergence of Federated Learning? Incentive Mechanism Design for Federated Learning with Unstateful Clients Incentive Analysis for Agent Participation in Federated Learning
federated learning (FL)	Communication-Efficient Federated Learning via Sparse Training with Regularized Error Correction
Feedback-based optimization	Hierarchical Control of Distribution Grids with Application to Transmission-Distribution Fast Frequency Control
Filter stability	Regularity and Approximations for Partially Observed Stochastic Control and Applications to Learning
finite bit-rates	Remote robust state estimation problem
Finite State Machines	Non-Adaptive Multi-Stage Algorithm for Group Testing with Prior Statistics
finite-length regime	Finite-Length Coding Bounds via Guesswork
finite-time convergence analysis	Suppressing Overestimation in Q-Learning through Adversarial Behaviors
Fisher divergence	Robust Score-Based Quickest Change Detection
Fisher-Rao gradient flow	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
Foundation Models	Foundation Models for Robotic Manipulation: Opportunities and Challenges
frequency moment	Differentially Private Space-Efficient Algorithms for Frequency Moment Estimation in the Turnstile Model
FSMC	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
Function approximation	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
functional compression	Multi-Functional Distributed Computing
G
Game Theory	Strategic Quantization with Quadratic Distortion Measures Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network Linearly Solvable General-Sum Markov Games Constrained Correlated Equilibria On the role of network structure in learning to coordinate with bounded rationality Tractable Equilibrium Computation in Markov Games through Risk Aversion Incentive Mechanism Design for Federated Learning with Unstateful Clients
Gates	New methods for quantum circuit synthesis with symmetry-respecting gates
Gauge group	GNarsil: Splitting Stabilizers into Gauges
Gaussian channels	On the Capacity of Scalar Gaussian Channels Subject to State Obfuscation
GDPR	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation
General-Sum Games	Linearly Solvable General-Sum Markov Games
Generalized games	Constrained Correlated Equilibria
generative modeling	Stochastic interpolants: A unifying framework for flows and diffusions
Geodesic Convexity	Structured Regularization for SPD Optimization with Side Information
Geometrically local quantum codes	Transform Arbitrary Good Quantum LDPC Codes into Good Geometrically Local Codes in Any Dimension
Gibbs channel	An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
Global convergence	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
global optimization	Minkowski Descent: An Algorithm for Stochastic Global Optimization
gradient descent optimization	Strategic Quantization with Quadratic Distortion Measures
gradient estimate	Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
Gradient Tracking	Communication-efficient and Decentralized Federated Minimax Optimization
Gram-Schmidt Orthogonalization	Beyond PCA: A Gram-Schmidt Approach to Feature Extraction
Graph Convolutional Neural Networks	Transferable Learning of GCN Sampling Graph Data Clusters from Different Power Systems
Graph Diffusion	Differentially Private Graph Diffusion with Applications in Personalized PageRanks
graph learning algorithm	Influence Chain Recovery and Application in Distributed Fact-Checking
graph-based learning	On the scalability of large graph methods for kernel-based machine learnin
Graphs	On the role of network structure in learning to coordinate with bounded rationality
Green's function	Weyl Calculus and Exactly Solvable Schrödinger Bridges with Quadratic State Cost
Grid-following control	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
grid-forming control	Grid-forming control of renewable generation and hybrid ac/dc power systems
grid-forming inverters	Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions
Group Testing (GT)	Non-Adaptive Multi-Stage Algorithm for Group Testing with Prior Statistics
Grover’s Search	Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better
guesswork	Finite-Length Coding Bounds via Guesswork
H
Hamilton-Jacobi-Bellman Equations	Scalable computations for nonlinear balanced truncation model reduction
Hazard rate	Caching or Pre-fetching? The Role of Hazard Rates
Heavy-traffic analysis	Transform Method for Markov-Modulated Queues
high-dimensional inference	OpAMP: Linear Regressions with Erasures
High-Dimensional Linear Models	Minimax Rate Optimal Algorithms For High-Dimensional Stochastic Linear Bandits
high-dimensional probability	OpAMP: Linear Regressions with Erasures
higher criticism	Higher-criticism for multi-sensor sparse change-point detection
higher-order optimization	Sharply predicting optimization trajectories in high-dimensions: State evolutions beyond first-order algorithms
Hopf bifurcation	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
Human-AI Collaboration	Learning to Defer in Content Moderation: The Human-AI Interplay
hybrid ac/dc power systems	Grid-forming control of renewable generation and hybrid ac/dc power systems
Hypothesis Testing	A Hypothesis Testing-based Framework for Cyber Deception with Sludging
I
ideal point model	Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Image compression	Lossless Binary Image Compression Using Learned Multi-level Dictionaries
Incentive analysis	Incentive Analysis for Agent Participation in Federated Learning
Incentive Mechanism	Incentive Mechanism Design for Federated Learning with Unstateful Clients
Incentivizing Exploration	Incentives for Exploration at Market Equilibrium
Index Coding	Restricted Converse Results for g-Group Complete-{s} Pliable Index Coding Problems
Inference	Post-Contextual Bandit Inference with Adaptive Stopping
infinite-horizon control	Optimal Infinite-Horizon Mixed $H_2 / H_\infty$ Control
Information density	Privacy-Utility Tradeoff Based on $\alpha$-lift
Information Falsification	A Hypothesis Testing-based Framework for Cyber Deception with Sludging
information geometry	An Information Geometric Analysis of Noise Contrastive Estimation
Information structure	Information Structures in AC/DC Grids
Information Theory	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation An Information Geometric Analysis of Noise Contrastive Estimation Restricted Converse Results for g-Group Complete-{s} Pliable Index Coding Problems
information-theoretic bounds	Sharp information-theoretic thresholds for shuffled linear regression Personalized Federated Learning with Shared Linear Representation: Statistically Optimal Rates
infrastructure planning	Braess’ Paradoxes in Electrified Transportation
Integer linear programming	Closing the Duality Gap on Integer Linear Programming
interior-point methods	Stochastic-Gradient-based Interior-Point Methods
interpretation	Higher-order Interpretations of Deepcode, a Learned Feedback Code
intervention	Sequential Design of Experiments in Causal Systems
inverse problems	Optimal Regularization for a Data Source
Inverter-based resources	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
inverters	Equivalent-circuit Modeling Framework to Facilitate Large-signal Stability Assessment of Inverter-based Resources
iSWAP	New methods for quantum circuit synthesis with symmetry-respecting gates
iterative algorithms	The Power Method with Row Erasures
Iterative decoding	Quantum LDPC Codes: Constructions and Decoders Handling Degeneracy Graph Codes for Dual-Parameter Barrier Channels
J
JCAS	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
K
kernel methods	On the scalability of large graph methods for kernel-based machine learnin
KNN	On the scalability of large graph methods for kernel-based machine learnin
Kron reduction	Reverse Kron Reduction on Trees
kronecker products	A sufficient condition for 2-contraction of a feedback interconnection
Kullback-Leibler divergence	Chernoff Information as a Privacy Constraint for Adversarial Classification
L
Lagrangian multipliers	Closing the Duality Gap on Integer Linear Programming
Langevin dynamic	Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
large language model	Adaptive Text Watermark for Large Language Models
Large Language Models	Self-Play Preference Optimization for Language Model Alignment Mitigating Backdoor Threats to Large Language Models
large linear systems	On the scalability of large graph methods for kernel-based machine learnin
Large-language models	Do LLM Agents Have Regret? A Case Study in Online Learning and Games
large-signal stability assessment	Equivalent-circuit Modeling Framework to Facilitate Large-signal Stability Assessment of Inverter-based Resources
Las layer retraining	Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
Learning	On the role of network structure in learning to coordinate with bounded rationality Nonlinear Filtering with Brenier Optimal Transport Maps
Learning for Control	Active Exploration for Minimax Estimation in MDPs
learning from people	Learning the eye of the beholder: Statistical modeling and estimation for personalized color perception
Learning in Markets	Incentives for Exploration at Market Equilibrium
linear convergence	Toward Parameter-free Decentralized Optimization
Linear regression	Sharp information-theoretic thresholds for shuffled linear regression OpAMP: Linear Regressions with Erasures
Linear systems	Minimum Data-Rate for Emulating a Linear Feedback System
linearly separable functions	Multi-Functional Distributed Computing
LLM	Reinforcement Learning from Human Feedback without Reward Inference
LLMs	Efficient LLM Serving via Lossy Computation
Local Updates	Communication-efficient and Decentralized Federated Minimax Optimization
Local Volt/Var control	Stability-Constrained Voltage Control in Distribution Grids
Long Context	Efficient LLM Serving via Lossy Computation
Lossless compression	Lossless Binary Image Compression Using Learned Multi-level Dictionaries
Lossy Computation	Efficient LLM Serving via Lossy Computation
Low-rank matrix recovery	Metric Clustering From Triplet Comparisons Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion
Lyapunov function	Opportunistic Learning for Markov Decision Systems with Application to Smart Robots Lyapunov-like converse result for strong forward invariance
Lyapunov methods	Remote robust state estimation problem
Lyapunov stability	Stability-Constrained Voltage Control in Distribution Grids
M
machine learning	A Masked Pruning-Based Algorithm for Dimensionality Reduction in Federated Learning Systems Quickest Change Detection Using Mismatched CUSUM Stochastic-Gradient-based Interior-Point Methods
machine learning theory	Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls
Machine unlearning	Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
Malicious nodes
MAP	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
Margulis code	Quantum Margulis Codes
Market Equilibrium	Incentives for Exploration at Market Equilibrium
Markov Chains	Markov Chain Variance Estimation: A Stochastic Approximation Approach
Markov decision process	Traffic-driven Spectrum and Power Allocation via Scalable Multi-agent Reinforcement Learning Localized spectral representations for reinforcement learning in networked MDPs A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
Markov Games	Linearly Solvable General-Sum Markov Games
Markov Processes	Non-Adaptive Multi-Stage Algorithm for Group Testing with Prior Statistics
Markov-modulated arrivals	Transform Method for Markov-Modulated Queues
maximal correlation	Dependence Induced Representations
Maximum likelihood estimation	Sharp information-theoretic thresholds for shuffled linear regression
method of moments	Personalized Federated Learning with Shared Linear Representation: Statistically Optimal Rates
metric learning	Metric Clustering From Triplet Comparisons Pluralistic Alignment Framework for Learning from Heterogeneous Preferences Learning the eye of the beholder: Statistical modeling and estimation for personalized color perception
minimal sufficiency	Dependence Induced Representations
Minimax Rate	Minimax Rate Optimal Algorithms For High-Dimensional Stochastic Linear Bandits
minimum distance	Robust Distribution Estimation via Partial Optimal Transport
Minkowski sums	Minkowski Descent: An Algorithm for Stochastic Global Optimization
Mirror descent	Value Mirror Descent For Reinforcement Learning
Mirror descent method	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
misinformation	Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network
mixed $H_2 / H_\infty$ control	Optimal Infinite-Horizon Mixed $H_2 / H_\infty$ Control
Mobility	Mobility in Age-Based Gossip Networks
Model-identification	Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
monogamy of entanglement	On Non-Local Coset Guessing Quantum Games
Monotone system theory	Reachability Analysis of Dynamical Systems: A Mixed Monotone Contracting Approach
Multi-agent MDP	Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Multi-agent Network Systems	Localized spectral representations for reinforcement learning in networked MDPs
Multi-Agent Reinforcement Learning	Tractable Equilibrium Computation in Markov Games through Risk Aversion
multi-agent reinforcement learning (MARL)	Traffic-driven Spectrum and Power Allocation via Scalable Multi-agent Reinforcement Learning
Multi-agent systems	Locally Interdependent Multi-Agent MDP: Theoretical Framework for Decentralized Agents with Dynamic Dependencies
Multi-armed Bandits	Learning to Defer in Content Moderation: The Human-AI Interplay
multi-start	Minkowski Descent: An Algorithm for Stochastic Global Optimization
Multiagent network systems	Classification with a Network of Partially Informative Agents: Enabling Wise Crowds from Individually Myopic Classifiers
multiple timescales	Minkowski Descent: An Algorithm for Stochastic Global Optimization
multistability	A sufficient condition for 2-contraction of a feedback interconnection
multistationarity	A sufficient condition for 2-contraction of a feedback interconnection
N
Nash equilibrium	Fairness of Equilibrium in Proportional Sharing Mechanisms with Bid Costs Non-Monotone Variational Inequalities
Natural gradient method	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
Network control	A synthesis approach for distributed H2 control problems with communication delays On the role of network structure in learning to coordinate with bounded rationality
Network games	Designing interventions in multi-activity network games for forest resource management
networked control systems	Control with minimum data-transmission
Networked systems	Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
neural collapse	Dependence Induced Representations
neuroscience	Understanding Neural Population Communication with Latent Channels
noise contrastive estimation	An Information Geometric Analysis of Noise Contrastive Estimation
non-coherent communications	On the Capacity of Scalar Gaussian Channels Subject to State Obfuscation
Non-convex optimization	A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
non-local games	On Non-Local Coset Guessing Quantum Games
Non-monotone VI	Non-Monotone Variational Inequalities
non-parametric statistics	Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls Higher-criticism for multi-sensor sparse change-point detection
Nonconvex optimization	Closing the Duality Gap on Integer Linear Programming Distributed Difference of Convex Optimization Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion
Nonlinear Filtering	Nonlinear Filtering with Brenier Optimal Transport Maps
nonlinear functions	Multi-Functional Distributed Computing
Nonlinear system	Generalized Barrier Functions: Integral Conditions & Recurrent Relaxations
Nonlinear systems	Nonlinear observers with online error bounds On topological entropy of switched cascade systems
nonnegative supermartingale	Power-one sequential tests, confidence sequences, e-processes and e-detectors
Nonsmooth stochastic approximation	Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation
Normal vectors	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
Numerical optimization	Specialized Numerical Optimization Algorithms for QIS
O
oblivious transfer	SPIR with Colluding and Non-Replicated Servers from a Noisy Channel
Observer design	Nonlinear observers with online error bounds
offline reinforcement learning	Achieving the Asymptotically Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach
one-way marginals	Differential Privacy and Sublinear Time are Incompatible Sometimes
Online decision-making	Instance-Optimality in Online Learning
Online learning	Instance-Optimality in Online Learning Do LLM Agents Have Regret? A Case Study in Online Learning and Games
Online optimization	Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
operator algebra	Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction
opinion dynamics	Shaping opinions in social networks with shadow banning
Optimal Control	A synthesis approach for distributed H2 control problems with communication delays Linear-time Scheduling for Time-varying Wireless Networks via Randomization
optimal noise	Optimized Mechanisms for Differentially Private Composition
Optimal Power Flow	Exploring Feasible Transition from Local to Global Optima in Power Systems
optimal sample complexity	Personalized Federated Learning with Shared Linear Representation: Statistically Optimal Rates
Optimal transport	Differentially Private Sinkhorn Algorithm Distributionally Robust Optimal Transport for Improved Model Robustness Robust Distribution Estimation via Partial Optimal Transport
Optimal Transportation	Nonlinear Filtering with Brenier Optimal Transport Maps
optimization	Opportunistic Learning for Markov Decision Systems with Application to Smart Robots A synthesis approach for distributed H2 control problems with communication delays How Do System Dynamics Affect the Convergence of Federated Learning?
Optimization in Networks	Designing interventions in multi-activity network games for forest resource management
optimization-based control design	Control with minimum data-transmission
Oscillations	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
overestimation bias	Suppressing Overestimation in Q-Learning through Adversarial Behaviors
P
Packet Drops	Acknowledgment Feedback in Directed Graphs via Deterministic and Probabilistic Strategies
PageRanks	Differentially Private Graph Diffusion with Applications in Personalized PageRanks
Parameter sensitivity	Sensitivity to Hopf Bifurcation in Grid-Following Inverters Using Normal Vector Methods
partial correction	Authenticated partial correction over AV-MACs: toward characterization and coding
Partially observed control	Regularity and Approximations for Partially Observed Stochastic Control and Applications to Learning
Peer-to-peer network	Classification with a Network of Partially Informative Agents: Enabling Wise Crowds from Individually Myopic Classifiers
Physical World	From Large Language Models to Large Agent Models: Planning and Reasoning with Physical World Knowledge
Physical-layer security and privacy	On the Capacity of Scalar Gaussian Channels Subject to State Obfuscation
Pliable Index Coding	Restricted Converse Results for g-Group Complete-{s} Pliable Index Coding Problems
Polynomial Codes	A New Framework for Designing Polynomial Codes for Private Information Retrieval
posterior sampling	On solving inverse problems in computer vision using latent diffusion models
potential function	collaborative exploration of unknown environments
Power Grid	Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
Power Grid Universal Learning	Transferable Learning of GCN Sampling Graph Data Clusters from Different Power Systems
power method	The Power Method with Row Erasures
power system dynamics	Grid-forming control of renewable generation and hybrid ac/dc power systems
power systems	Exploring Feasible Transition from Local to Global Optima in Power Systems Fair-Over-Time Distributed Energy Resource Coordination Balancing Fairness and Efficiency in Power Systems with Large and Small Users Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions
Power systems control	Hierarchical Control of Distribution Grids with Application to Transmission-Distribution Fast Frequency Control
power-one tests	Power-one sequential tests, confidence sequences, e-processes and e-detectors
Pre-fetching	Caching or Pre-fetching? The Role of Hazard Rates
predictive coding	Temporal Predictive Coding for Gradient Compression in Distributed Learning
preference learning	Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
Preference Optimization	Self-Play Preference Optimization for Language Model Alignment
Prelimit coupling	Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation
Price of anarchy	Fairness of Equilibrium in Proportional Sharing Mechanisms with Bid Costs Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network
Principal Component Analysis	Beyond PCA: A Gram-Schmidt Approach to Feature Extraction
Privacy	You Shall Not Leak Your Brother's Data: Privacy Control in the Presence of Correlation Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
privacy leakage	Differential Privacy in the Large Composition Regime
Privacy-utility trade-off	Privacy-Utility Tradeoff Based on $\alpha$-lift
Privacy-utility tradeoff	Differentially Private Sinkhorn Algorithm
private information retrieval	SPIR with Colluding and Non-Replicated Servers from a Noisy Channel
Private Information Retrieval (PIR)	A New Framework for Designing Polynomial Codes for Private Information Retrieval
Private Linear Computation	A New Framework for Designing Polynomial Codes for Private Information Retrieval
probabilistic graphical models	Influence Chain Recovery and Application in Distributed Fact-Checking
Probability Sampling	Harmonic Path Integral Diffusion
product channel	Contraction Coefficients of Product Symmetric Channels
Proportionally fair resource allocation	Fairness of Equilibrium in Proportional Sharing Mechanisms with Bid Costs
Pruning algorithms	A Masked Pruning-Based Algorithm for Dimensionality Reduction in Federated Learning Systems
Q
Q-learning	Suppressing Overestimation in Q-Learning through Adversarial Behaviors Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation The Sample-Communication Complexity Trade-off in Federated Q-Learning
Q-Value Function	Localized spectral representations for reinforcement learning in networked MDPs
Quadratic assignment problems	Sharp information-theoretic thresholds for shuffled linear regression
quadratic optimization	An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
quantization	Strategic Quantization with Quadratic Distortion Measures
Quantized systems	Minimum Data-Rate for Emulating a Linear Feedback System
Quantum algorithms	Feedback-based quantum algorithms: Extensions to real-time feedback CANOE: The Classically Assisted Non-Orthogonal Eigensolver
quantum chemistry	CANOE: The Classically Assisted Non-Orthogonal Eigensolver
Quantum chip design	Specialized Numerical Optimization Algorithms for QIS
Quantum Circuits	New methods for quantum circuit synthesis with symmetry-respecting gates
quantum codes	Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction
quantum computing	Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation Solving the B-SAT Problem Using Quantum Computing: Smaller is Sometimes Better Feedback-based quantum algorithms: Extensions to real-time feedback CANOE: The Classically Assisted Non-Orthogonal Eigensolver
Quantum Control	Feedback-based quantum algorithms: Extensions to real-time feedback
quantum erasure channel	Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation
quantum error correction	GNarsil: Splitting Stabilizers into Gauges Quantum LDPC Codes: Constructions and Decoders Handling Degeneracy Binary Triorthogonal and CSS-T Codes for Quantum Error Correction Quantum Margulis Codes Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction
quantum error-correcting codes	Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation
Quantum Fisher information	Specialized Numerical Optimization Algorithms for QIS
Quantum Information Theory	Transform Arbitrary Good Quantum LDPC Codes into Good Geometrically Local Codes in Any Dimension
Quantum LDPC	Quantum Margulis Codes
quantum low-density parity check codes	Quantum LDPC Codes: Constructions and Decoders Handling Degeneracy
Quantum low-density parity-check codes	Transform Arbitrary Good Quantum LDPC Codes into Good Geometrically Local Codes in Any Dimension
Quantum State Discrimination	Acceptance in Postselected Asymptotic Quantum State Discrimination
Queueing Theory	Learning to Defer in Content Moderation: The Human-AI Interplay
Quickest change detection	Private Online Community Detection for Censored Block Models
R
Random geometric graphs	Impossibility of latent inner product recovery via rate distortion
Randomized Algorithms	Linear-time Scheduling for Time-varying Wireless Networks via Randomization
rank minimization	Control with minimum data-transmission
Rate-distortion function	Impossibility of latent inner product recovery via rate distortion
Reachability analysis	Reachability Analysis of Dynamical Systems: A Mixed Monotone Contracting Approach
recurrent neural networks	Traffic-driven Spectrum and Power Allocation via Scalable Multi-agent Reinforcement Learning
redundancy	Optimal Redundancy in Exact Channel Synthesis
regularization	Structured Regularization for SPD Optimization with Side Information Optimal Regularization for a Data Source
Reinforcement learning	Suppressing Overestimation in Q-Learning through Adversarial Behaviors Linearly Solvable General-Sum Markov Games Regularity and Approximations for Partially Observed Stochastic Control and Applications to Learning Value Mirror Descent For Reinforcement Learning Reinforcement Learning from Human Feedback without Reward Inference A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces Active Exploration for Minimax Estimation in MDPs Solving Markov Decision Processes via Reward Balancing
Reinforcement Learning from Human Feedback	Self-Play Preference Optimization for Language Model Alignment
remote state estimation	Remote robust state estimation problem
representation learning	Dependence Induced Representations Personalized Federated Learning with Shared Linear Representation: Statistically Optimal Rates
Resilience
Richardson-Romberg extrapolation	Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation
Riemannian optimization	Structured Regularization for SPD Optimization with Side Information
Risk Aversion	Tractable Equilibrium Computation in Markov Games through Risk Aversion
Risk-sensitive RL	Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
RLHF	Reinforcement Learning from Human Feedback without Reward Inference
Robot Learning	Foundation Models for Robotic Manipulation: Opportunities and Challenges
Robotic Manipulation	Foundation Models for Robotic Manipulation: Opportunities and Challenges
Robust	Robust Conditional Value-at-Risk Based Risk-Sensitive Reinforcement Learning
robust control	Optimal Infinite-Horizon Mixed $H_2 / H_\infty$ Control
Robust Federated Learning	Communication-efficient and Decentralized Federated Minimax Optimization
robust reinforcement learning	Achieving the Asymptotically Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach
robust statistics	A robust testing approach to measuring model varability Robust Distribution Estimation via Partial Optimal Transport
Robust tests	Robust Score-Based Quickest Change Detection
robustness	Adaptive Text Watermark for Large Language Models
Rényi divergence	Optimized Mechanisms for Differentially Private Composition
S
Safety	Generalized Barrier Functions: Integral Conditions & Recurrent Relaxations
Sample complexity	Value Mirror Descent For Reinforcement Learning The Sample-Communication Complexity Trade-off in Federated Q-Learning
Sampling Algorithms	Harmonic Path Integral Diffusion
Scheduling	Linear-time Scheduling for Time-varying Wireless Networks via Randomization
Schrödinger bridge	Weyl Calculus and Exactly Solvable Schrödinger Bridges with Quadratic State Cost
Schur complement	Reverse Kron Reduction on Trees
Secret Sharing	Distributed Matrix Multiplication: Download Rate, Randomness and Privacy Trade-Offs
Secure Distributed Matrix Multiplication	Distributed Matrix Multiplication: Download Rate, Randomness and Privacy Trade-Offs
Self Play	Self-Play Preference Optimization for Language Model Alignment
Semi-parametric statistics	Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls
sequential	Sequential Design of Experiments in Causal Systems
sequential change detection	Power-one sequential tests, confidence sequences, e-processes and e-detectors
sequential estimation	Power-one sequential tests, confidence sequences, e-processes and e-detectors
sequential testing	Power-one sequential tests, confidence sequences, e-processes and e-detectors
Set invariance	Generalized Barrier Functions: Integral Conditions & Recurrent Relaxations
shadow banning	Shaping opinions in social networks with shadow banning
Shannon theory	On the Capacity of Scalar Gaussian Channels Subject to State Obfuscation
Shapley-Folkman theorem	Minkowski Descent: An Algorithm for Stochastic Global Optimization
single-index models	Robustly Learning Single-Index Models via Alignment Sharpness
Sinkhorn algorithm	Differentially Private Sinkhorn Algorithm
skewed statistics	Multi-Functional Distributed Computing
slow learning	Characterization of Slow Convergence in Word-of-Mouth Social Learning
Sludging	A Hypothesis Testing-based Framework for Cyber Deception with Sludging
social learning	Characterization of Slow Convergence in Word-of-Mouth Social Learning
social network	Price of Anarchy of a Censorship Policy removing Misinformation in a Social Network
social networks	Shaping opinions in social networks with shadow banning
Solovay-Kitaev theorem	New methods for quantum circuit synthesis with symmetry-respecting gates
Sparse Signal Recovery	Non-Adaptive Multi-Stage Algorithm for Group Testing with Prior Statistics
sparse training	Communication-Efficient Federated Learning via Sparse Training with Regularized Error Correction
SPD manifold	Structured Regularization for SPD Optimization with Side Information
Spectral Representation	Localized spectral representations for reinforcement learning in networked MDPs
stabilizer formalism	Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction
star bodies	Optimal Regularization for a Data Source
state evolution	Sharply predicting optimization trajectories in high-dimensions: State evolutions beyond first-order algorithms
statistical dependence	Dependence Induced Representations
statistical estimation	Learning the eye of the beholder: Statistical modeling and estimation for personalized color perception
Statistical limits	Sharp information-theoretic thresholds for shuffled linear regression
Steady-state convergence	Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive Stochastic Approximation
stochastic algorithms	Solving Markov Decision Processes via Reward Balancing
Stochastic Approximation	Markov Chain Variance Estimation: A Stochastic Approximation Approach
Stochastic Bandits	Minimax Rate Optimal Algorithms For High-Dimensional Stochastic Linear Bandits
Stochastic block coordinate descent	Differentially Private Sinkhorn Algorithm
stochastic block models	Private Online Community Detection for Censored Block Models
stochastic control	Opportunistic Learning for Markov Decision Systems with Application to Smart Robots
stochastic gradient methods	Stochastic-Gradient-based Interior-Point Methods
Stochastic Hybrid Systems	Mobility in Age-Based Gossip Networks
Stochastic Optimal Control	Harmonic Path Integral Diffusion
stochastic traffic	Traffic-driven Spectrum and Power Allocation via Scalable Multi-agent Reinforcement Learning
strong data processing inequality	Contraction Coefficients of Product Symmetric Channels
strong invariance	Lyapunov-like converse result for strong forward invariance
structure learning	Influence Chain Recovery and Application in Distributed Fact-Checking
sublinear algorithms	Differential Privacy and Sublinear Time are Incompatible Sometimes
sublinear space	Differentially Private Space-Efficient Algorithms for Frequency Moment Estimation in the Turnstile Model
Subsystem codes	GNarsil: Splitting Stabilizers into Gauges
Sustainability	Designing interventions in multi-activity network games for forest resource management
Switched systems	On topological entropy of switched cascade systems
symmetric channel	Contraction Coefficients of Product Symmetric Channels
symmetric private information retrieval	SPIR with Colluding and Non-Replicated Servers from a Noisy Channel
Symmetrized KL information	An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
Symmetry	New methods for quantum circuit synthesis with symmetry-respecting gates
Symplectic basis	GNarsil: Splitting Stabilizers into Gauges
synthetic data	Training Language Models on Private Federated Data in the Age of LLMs
T
text-guided image editing	On solving inverse problems in computer vision using latent diffusion models
Throughput	Strategies for Rate Optimization in Joint Sensing and Communication over Channels with Memory
Topological entropy	On topological entropy of switched cascade systems
Transform Method	Transform Method for Markov-Modulated Queues
Transportation electrification	Braess’ Paradoxes in Electrified Transportation
tree exploration	collaborative exploration of unknown environments
Tree networks	Reverse Kron Reduction on Trees
triorthogonal code	Binary Triorthogonal and CSS-T Codes for Quantum Error Correction
Tunable privacy measures	Privacy-Utility Tradeoff Based on $\alpha$-lift
turnstile	Differentially Private Space-Efficient Algorithms for Frequency Moment Estimation in the Turnstile Model
two-block group algebra codes	Quantum Margulis Codes
Type-1 and Type-2 Error	Acceptance in Postselected Asymptotic Quantum State Discrimination
U
unbalanced faults	Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions
Uncertainty quantification	Nonlinear observers with online error bounds
unclonable cryptography	On Non-Local Coset Guessing Quantum Games
Universal Adversarial Perturbation	Communication-efficient and Decentralized Federated Minimax Optimization
unnormalized and score-based models	Robust Score-Based Quickest Change Detection
V
Variance Estimation	Markov Chain Variance Estimation: A Stochastic Approximation Approach
Ville's inequality	Power-one sequential tests, confidence sequences, e-processes and e-detectors
Vision-Language	From Large Language Models to Large Agent Models: Planning and Reasoning with Physical World Knowledge
Viterbi Algorithm (VA)	Non-Adaptive Multi-Stage Algorithm for Group Testing with Prior Statistics
Voltage source converter	Information Structures in AC/DC Grids
W
Wasserstein distance	Robust Distribution Estimation via Partial Optimal Transport
watermarking	Adaptive Text Watermark for Large Language Models
Weak Coupling	Non-Monotone Variational Inequalities
Weyl calculus	Weyl Calculus and Exactly Solvable Schrödinger Bridges with Quadratic State Cost
Wireless Networks	Traffic-driven Spectrum and Power Allocation via Scalable Multi-agent Reinforcement Learning Linear-time Scheduling for Time-varying Wireless Networks via Randomization
Wishart distribution	Impossibility of latent inner product recovery via rate distortion
worst group accuracy	Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
X
XY interaction	New methods for quantum circuit synthesis with symmetry-respecting gates
Z
zero-order	Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
zero-sum game	Suppressing Overestimation in Q-Learning through Adversarial Behaviors

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