2026 ALLERTON: 62ND ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING

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

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$\alpha$-I-MMSE relationship	$\alpha$-Mutual Information for the Gaussian Noise Channel
$\alpha$-mutual information	$\alpha$-Mutual Information for the Gaussian Noise Channel
2
2.5D/3D integration	PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions
3
3D generative models	Online World Modeling for Closed-Loop Planning Under Partial Observability
3D reconstruction	Beyond Photorealism: 3D Reconstruction and Generation with Multimodal and Physical Grounding
5
5G/6G	AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents
A
AC optimal power flow	Low-Rank and Lifted Semidefinite Programming for Global MINLP Power Grid Optimization
active inference
Adaptive estimation	Adaptive Minimax Estimation Across SNR Regimes
adaptive stepsize	Adaptive Decentralized Optimization
adjoint-free	Data-Efficient Learning for Asymptotically Smooth Integral Operators
Adversarial Attack	Compromising Offline RLHF: An Efficient Preference Poisoning Approach
adversarial detection	Robust and Adversarial Sequential Change-Point Detection in High Dimensions
Adversarial Errors	Secret key-distribution over networks with node-based adversarial errors
Adversary	Adaptive Decentralized Learning in Adversary-Dominated Settings
Age of information	Analysis and Optimization of Age of Information in Large-Scale Random Access Networks
Agentic capabilities	PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost
AI	AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents
AI detection	In-Context Watermarks for Large Language Models
algebraic decoding
Analog Coding	Few-Shot Universal Analog Communication
annealed Markov chains	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
anti-correlation	Cross-Validation Error Dynamics in Smaller Datasets
approximate message passing	Operator-Norm Robust LASSO: A Precise Analysis and an AMP-style Algorithm
assortment optimization	Optimal Exploration of New Products under Assortment Decisions
atomic norms	Improved Convex Relaxations for Simultaneously Sparse and Quantized Signal recovery
attention models	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
autoencoders	Limitations and capabilities of autoencoders for learning dynamics
average run length	Sequential Change Detection with Differential Privacy
B
Bandits	Tail-Aware Bandits: Optimal Rules and Algorithm
Base Station Deployment	Stochastic Geometry meets Optimization: Soft Deployment in Cellular Networks
Bayesian Games	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
Bayesian online resource allocation	Prophet Inequalities with Cancellation Costs
Bayesian Persuasion	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap Embodied Persuasion: Information Design and Physical Leakage in Markov Games
BCH codes	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Behavioral systems theory	Trusting and Adapting Data-Driven Predictors for Control Behavioral System Theory for Dynamic Optimization
Bellman operator	Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Unified Bellman-Operator Framework
Biological Sequence learning	From Sequence to Signature: Infinite-Order Signature Kernels for Biological Sequence Learning
Birkhoff polytope	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
Buyback problem	Prophet Inequalities with Cancellation Costs
C
cancer treatment
car-following control
Carrier Sensing	Analysis and Optimization of Age of Information in Large-Scale Random Access Networks
Central limit theorem	Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains
channels with states	Impact of State Knowledge on Covert Communication in the Presence of Simultaneous Transmission
closed-loop planning	Online World Modeling for Closed-Loop Planning Under Partial Observability
Co-design	Learning to Design Robots
Combinatorial geometry	Quantifying Classification Performance using Combinatorial Geometry and Local Data Analysis
Commitment	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
communication complexity	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
Communication efficiency	Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks
Communication-computation resource-efficiency	Budget-Constrained Multi-Consensus Decentralized Gradient Descent
Competitive Analysis	Water-filling is Universally Minimax Optimal
Complexity	Universal Parameter-Free First-Order Algorithms for Convex Optimization
compositional generalization	Toward Compositional Generalization in the Physical World
Computational Security	Revisiting SPIR-Based PSI: A Computational Perspective
conditional computation	The Information Needs of Robot Learners
constrained MDPs	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
constraints	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
contingency analysis	A Single ML Model for Predicting AC Power Flow Solutions under Line Contingencies
Continuous Optimization	Universal Parameter-Free First-Order Algorithms for Convex Optimization
Control	Affiliated operators for classical and quantum control The robustness of games as models in multi-agent control: studying stability and sensitivity to misspecification Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
Controllability of diffeomorphism	On Controllability of Diffeomorphisms
Convergence rate	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence Adaptive Decentralized Optimization
Convex Gaussian min–max theorem	Operator-Norm Robust LASSO: A Precise Analysis and an AMP-style Algorithm
Convex hull pricing	Copositive characterization of convex hull pricing
Convex optimization	Budget-Constrained Multi-Consensus Decentralized Gradient Descent
convex relaxations	Improved Convex Relaxations for Simultaneously Sparse and Quantized Signal recovery
convex stochastic order	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
Coordination Games	Learning to Coordinate over Networks with Heterogeneous Rationalities
Copositive programming	Copositive characterization of convex hull pricing
Counterclockwise dissipativity	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
covariance matrix	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
covert communications	Impact of State Knowledge on Covert Communication in the Presence of Simultaneous Transmission
cross-domain adaptation	Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
cross-embodiment transfer	Toward Compositional Generalization in the Physical World
cross-validation	Cross-Validation Error Dynamics in Smaller Datasets
CSI feedback	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
CuSum procedure	Sequential Change Detection with Differential Privacy
D
Data	What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty
Data driven Decision making	What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty
data fusion	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
Data Imbalance	When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?
Data-driven control	Trusting and Adapting Data-Driven Predictors for Control Behavioral System Theory for Dynamic Optimization On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees On data-driven control of linear systems with quantized data
decentralized control systems	Verifiably Safe Decentralized Control via Event-Triggered Topology Switching
Decentralized Learning	Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback Convergence of Fictitious Play in a Class of Product Markov Games
decentralized optimization	Budget-Constrained Multi-Consensus Decentralized Gradient Descent Adaptive Decentralized Learning in Adversary-Dominated Settings Adaptive Decentralized Optimization
Deception and Privacy	The Rate-Distortion-Deception Tradeoff
deep neural networks	A Single ML Model for Predicting AC Power Flow Solutions under Line Contingencies
deep reinforcement learning	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
deep relays	Improving Confidentiality in Wireless Networks with Non-Linear Relays and Deep-Learning
delayed feedback	Remote IoT Source Monitoring with Delayed Feedback
Demand Response	Regret-Optimal Safe Adaptive Control under Chance Constraints: Application to Thermostatically Controlled Loads
detection delay	Sequential Change Detection with Differential Privacy
dexterous manipulation	Toward Compositional Generalization in the Physical World
difference of convex	Frechet Regression on Curved Manifolds
differential privacy	Differentially Private Selection using Enhanced Sensitivity Concepts Sequential Change Detection with Differential Privacy
differential topology	Limitations and capabilities of autoencoders for learning dynamics
diffusion	Faster Diffusion Language Models Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
Diffusion Model	On the Efficiency of GRPO and the Generalization of Diffusion Models
diffusion models	Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo Are Normalizing Flows Good Candidates for Interactive World Models? Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics Learnable Chernoff Baselines for Provable Inference-Time Alignment Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
diffusion policy	Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
Dimension reduction	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
dirty paper coding	Impact of State Knowledge on Covert Communication in the Presence of Simultaneous Transmission
discrete diffusion	Test-Time Anchoring for Discrete Diffusion Posterior Sampling
distributed and large-scale systems	Verifiably Safe Decentralized Control via Event-Triggered Topology Switching
Distributed Energy Resources
distributed estimation	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
Distributed learning	Distributed 20 Questions for Classification
Distributed Optimization	Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks High Probability Bounds for Stochastic Optimization Algorithms
diversity
diversity-aware routing	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
Doubly smoothed policy iteration	Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Unified Bellman-Operator Framework
Duality	Copositive characterization of convex hull pricing
dynamic games	Strategically Robust Dynamic Games
Dynamic games with symmetric information	Reasoning and learning to play against passive and reactive agents
Dynamic Networked Microgrids	Reconfiguration and Real-Time Control of Networked Microgrids Under Load Uncertainty
dynamic optimization	Behavioral System Theory for Dynamic Optimization
Dynamical System
Dynamical systems	Affiliated operators for classical and quantum control Limitations and capabilities of autoencoders for learning dynamics
E
edge devices	Modulated learning for private and distributed regression with just a single sample per client device
Effective Dimension	Fisher Simplicity in KANs and MLPs
Efficient Concentration	Efficient Concentration through Stein's Method: An Illustration in Abandonment Queues
Eigenspace-Based Clustering	Eigenspace-Based Clustering for Personalized System Identification
eigenvalues	Observability conditions for neural state-space models with eigenvalues and their roots of unity
elliptic PDE	Data-Efficient Learning for Asymptotically Smooth Integral Operators
empirical processes	Temporal Rank Statistics under Markov Dependence
encoding dynamics	Limitations and capabilities of autoencoders for learning dynamics
end-to-end learning	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
Energy efficiency	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework
Equilibrium	Preference Aggregation in the Age of AI
Equilibrium Computation	Convergence of Fictitious Play in a Class of Product Markov Games
Equilibrium selection	Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback
ER graphs	Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
Error correction codes	Adversarially Robust Multiclass Classification via Error Correction Output Codes
error dynamics	Cross-Validation Error Dynamics in Smaller Datasets
Error-correcting output codes	Distributed 20 Questions for Classification
estimator selection	Adaptive Minimax Estimation Across SNR Regimes
event-trigger control	Verifiably Safe Decentralized Control via Event-Triggered Topology Switching
Evolutionary dynamics	Kullback-Leibler Divergence Regularized Learning (KLD-RL) Dynamics in Population Games Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
Evolutionary game theory	Learning to Avoid Tragedies: Feedback-Evolving Games with Heterogeneous Learning Rules An ODE-based method for resource allocation in a multi-agent systems
exchangeable random variables	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
F
factor graphs	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Fair allocation	Water-filling is Universally Minimax Optimal
Federated learning	Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks
feedback	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy
Few Shot Communication	Few-Shot Universal Analog Communication
Fictitious Play	Convergence of Fictitious Play in a Class of Product Markov Games Fictitious Play in Extensive-Form Games of Imperfect Information
First-Order	Universal Parameter-Free First-Order Algorithms for Convex Optimization
First-order differential equations	An ODE-based method for resource allocation in a multi-agent systems
First-order methods	A Proximal Descent Method for Nonconvex Policy Optimization
Fisher Information Matrix	Fisher Simplicity in KANs and MLPs
flash memory	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Flexible connection
flow matching	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
foundation models	A Graph Neural Network Foundation Model for AC Optimal Power Flow
Frechet regression	Frechet Regression on Curved Manifolds
free-energy principle
G
Game Theory	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework Kullback-Leibler Divergence Regularized Learning (KLD-RL) Dynamics in Population Games Career Concerns and Social Learning in Principal-Agent Environments Informal and Privatized Transit: Incentives, Efficiency and Coordination The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap The robustness of games as models in multi-agent control: studying stability and sensitivity to misspecification Learning to Coordinate over Networks with Heterogeneous Rationalities Fictitious Play in Extensive-Form Games of Imperfect Information
Gaussian noise channel	$\alpha$-Mutual Information for the Gaussian Noise Channel
Gaussian process bandits	Local and Global Approaches to Kernelized Bandit Optimization
Gaussian sequence model	Adaptive Minimax Estimation Across SNR Regimes
General-sum games
generation	Beyond Photorealism: 3D Reconstruction and Generation with Multimodal and Physical Grounding
Generative Modeling	Test-Time Anchoring for Discrete Diffusion Posterior Sampling Feedback Based Sampling using L2 Gradient Flows
generative models	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
genome statistics	Differentially Private Selection using Enhanced Sensitivity Concepts
Gibbs measures	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
global optimization	Low-Rank and Lifted Semidefinite Programming for Global MINLP Power Grid Optimization
Gradient Descent	Adaptive Decentralized Learning in Adversary-Dominated Settings
Gradient Flows	Feedback Based Sampling using L2 Gradient Flows
Gradient orthogonalization	Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization
graph matching	Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
graph neural networks	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing A Graph Neural Network Foundation Model for AC Optimal Power Flow
Graph Search	Optimal Incentive Contracting for Sensing and Searching for Rewards on a Graph
Green's Functions	Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment.
guided local search	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
H
H infinity control	Strategically Robust Dynamic Games
Hamiltonian systems	On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees
harmonic-aware estimation	Near-Field RIS-Assisted In-Cabin 3D Localization and Harmonic-Aware Vital Sign Estimation
Hartley Transform	Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment.
Hegselmann-Krause dynamics	Localmax Dynamics for Attention Models
Heterogeneous Dynamical Systems	Eigenspace-Based Clustering for Personalized System Identification
heterogeneous sensors	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
hierarchical matrix	Data-Efficient Learning for Asymptotically Smooth Integral Operators
High Probability Bounds	High Probability Bounds for Stochastic Optimization Algorithms
hybrid automatic repeat request	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy
I
Image classification	Adversarially Robust Multiclass Classification via Error Correction Output Codes
image editing	Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Incentive design	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
Incentives	Optimal Incentive Contracting for Sensing and Searching for Rewards on a Graph
incremental redundancy	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy
Inductive bias	On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees
inference-time alignment	Learnable Chernoff Baselines for Provable Inference-Time Alignment
infinite-dimensional systems	Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space
Informal transit	Informal and Privatized Transit: Incentives, Efficiency and Coordination
Information Design	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap Embodied Persuasion: Information Design and Physical Leakage in Markov Games
Information Disclosure	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
Information lattice learning	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
information leakage	A demonstration of information leakage via phase contamination
information theory	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
information-theoretic security	PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions
integral operator	Data-Efficient Learning for Asymptotically Smooth Integral Operators
intelligent networks	AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents
Interacting particle systems	Mean-shift interacting particle systems for sampling and quantization
interpretabile AI	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
Interpretability
interpretable machine learning	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
inverse problems	Test-Time Anchoring for Discrete Diffusion Posterior Sampling
IoT communications	Remote IoT Source Monitoring with Delayed Feedback
J
joint source-channel coding	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
K
Kernel learning	From Sequence to Signature: Infinite-Order Signature Kernels for Biological Sequence Learning
kernel methods	Robust and Adversarial Sequential Change-Point Detection in High Dimensions
Kernelized Bandit Optimization	Local and Global Approaches to Kernelized Bandit Optimization
KL-regularized MDP	Learnable Chernoff Baselines for Provable Inference-Time Alignment
Kolmogorov-Arnold networks (KAN)	Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
Kolmogorov-Arnold Networks (KANs)	Fisher Simplicity in KANs and MLPs
Koopman operator	Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space
Koopman operators	Affiliated operators for classical and quantum control
Kronecker-factored preconditioning	Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization
Kullback–Leibler divergence	Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization
L
Language models	Faster Diffusion Language Models
Large Language Model	Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Large language model pre-training	Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization
large language models	In-Context Watermarks for Large Language Models
Large load interconnection
large neighbourhood search	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
LDPC codes	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy
learning	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
Learning Algorithms	Learning to Coordinate over Networks with Heterogeneous Rationalities
learning for communications	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
Learning for Control	Regret-Optimal Safe Adaptive Control under Chance Constraints: Application to Thermostatically Controlled Loads
Learning in Games	Learning to Avoid Tragedies: Feedback-Evolving Games with Heterogeneous Learning Rules On the Necessity of Pricing to Steer Nonatomic No-Regret Agents to a Desired Bayes Correlated Equilibrium Fictitious Play in Extensive-Form Games of Imperfect Information
Learning in large populations	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
linear error-correcting codes	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
linear quadratic regulation
Linear separability	Quantifying Classification Performance using Combinatorial Geometry and Local Data Analysis
link layer transmission policies	Remote IoT Source Monitoring with Delayed Feedback
LLM	On the Efficiency of GRPO and the Generalization of Diffusion Models
LLMs	PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost
Load balancing	Load Balancing with Partial Queue Information: Threshold Optimality and Indexability Efficient Concentration through Stein's Method: An Illustration in Abandonment Queues
Local data analysis	Quantifying Classification Performance using Combinatorial Geometry and Local Data Analysis
Local dependence	Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains
Local polynomial estimators	Local and Global Approaches to Kernelized Bandit Optimization
localization	Near-Field RIS-Assisted In-Cabin 3D Localization and Harmonic-Aware Vital Sign Estimation
locally recoverable codes	Constructing Reed–Solomon Codes with Sparse Parity Checks
lookup-tables	PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions
Lossy source coding	The Rate-Distortion-Deception Tradeoff
low rank SDP	Low-Rank and Lifted Semidefinite Programming for Global MINLP Power Grid Optimization
low-latency transmission	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
low-rank estimation	Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
Low-rank sketching	Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks
Lyapunov methods	On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees On data-driven control of linear systems with quantized data
Lyapunov stability	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
M
machine learning	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy Adversarially Robust Multiclass Classification via Error Correction Output Codes
Machine learning and control
Mamba	Observability conditions for neural state-space models with eigenvalues and their roots of unity
Markov Chains	Learning to Coordinate over Networks with Heterogeneous Rationalities Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains
Markov decision process
Markov dependence	Temporal Rank Statistics under Markov Dependence
Markov Games	Embodied Persuasion: Information Design and Physical Leakage in Markov Games Convergence of Fictitious Play in a Class of Product Markov Games
Markov Perfect Equilibrium	Reasoning and learning to play against passive and reactive agents
martingale couplings	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
masked diffusion	Test-Time Anchoring for Discrete Diffusion Posterior Sampling
massive MIMO	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
matrix approximation	Data-Efficient Learning for Asymptotically Smooth Integral Operators
matrix-free optimization	Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
maximum entropy	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Maximum mean discrepancy	Mean-shift interacting particle systems for sampling and quantization
Mean Field	Analysis and Optimization of Age of Information in Large-Scale Random Access Networks
Mean shift	Mean-shift interacting particle systems for sampling and quantization
Mean-Field Control	Path-Integral Diffusion: From Generative AI and Interacting Agents to Quantum Measurements
Mean-field limit	Nonlinearity and Interaction in Schrödinger Bridges
Mechanism Design	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap On the Necessity of Pricing to Steer Nonatomic No-Regret Agents to a Desired Bayes Correlated Equilibrium
Metropolis algorithms	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
Min-max Optimization
minimax lower bounds	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
minimax risk	Adaptive Minimax Estimation Across SNR Regimes
mixing	Temporal Rank Statistics under Markov Dependence
Mixture optimality	Tail-Aware Bandits: Optimal Rules and Algorithm
mobile sensing	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
mode-switching controllers	The Information Needs of Robot Learners
Model-free Optimal Power Flow	Reconfiguration and Real-Time Control of Networked Microgrids Under Load Uncertainty
modulated learning	Modulated learning for private and distributed regression with just a single sample per client device
Moment method	Fast operator learning for mapping correlations
Multi-agent AI systems	An ODE-based method for resource allocation in a multi-agent systems
Multi-agent coordination	Kullback-Leibler Divergence Regularized Learning (KLD-RL) Dynamics in Population Games
Multi-agent learning	Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback
multi-agent reinforcement learning	Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
Multi-Agent Systems	Learning to Avoid Tragedies: Feedback-Evolving Games with Heterogeneous Learning Rules The robustness of games as models in multi-agent control: studying stability and sensitivity to misspecification
multi-armed bandit learning	Optimal Exploration of New Products under Assortment Decisions
Multi-class classification	Distributed 20 Questions for Classification
Multiclass classification	Adversarially Robust Multiclass Classification via Error Correction Output Codes
Multilayer Perceptrons (MLPs)	Fisher Simplicity in KANs and MLPs
Multiple Key-Cast	Secret key-distribution over networks with node-based adversarial errors
N
nash equilibrium	Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
Natural policy gradient	Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Unified Bellman-Operator Framework
near-field sensing	Near-Field RIS-Assisted In-Cabin 3D Localization and Harmonic-Aware Vital Sign Estimation
Near-potential functions
network alignment	Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
Network Coding	Secret key-distribution over networks with node-based adversarial errors
Network Secret Sharing	Secret key-distribution over networks with node-based adversarial errors
networked control systems
Networks	Learning to Coordinate over Networks with Heterogeneous Rationalities
neural networks	Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
neural ODE	Observability conditions for neural state-space models with eigenvalues and their roots of unity
Neural Operators	Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment.
neural video codec	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
non-linear codes	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
non-volatile memory	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Nonconvex problem	A Proximal Descent Method for Nonconvex Policy Optimization
nonlinear amplifiers	Improving Confidentiality in Wireless Networks with Non-Linear Relays and Deep-Learning
Nonlinear control	On Controllability of Diffeomorphisms
nonlinear systems	From Echo States to Dominant Manifolds: A Systems-Theoretic View of Reservoir Computing On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees
Nonlinear systems and control	Determining and Improving Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment and Preventive Action
normalizing flows	Are Normalizing Flows Good Candidates for Interactive World Models?
Nummelin’s splitting	Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains
O
Object tracking and grasping	Constrained Dynamic Grasping under Limited Visual Feedback
observability	Observability conditions for neural state-space models with eigenvalues and their roots of unity
off-dynamics reinforcement learning	Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
offline reinforcement learning	Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
Offline RLHF	Compromising Offline RLHF: An Efficient Preference Poisoning Approach
Online algorithms	Prophet Inequalities with Cancellation Costs Water-filling is Universally Minimax Optimal
online detection	Temporal Rank Statistics under Markov Dependence
only one privacy-sensitive sample per client	Modulated learning for private and distributed regression with just a single sample per client device
open networks	Source-Reliability Weighted Observer Design for Open Client–Server Networks
Open RAN	AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents
operator learning	Fast operator learning for mapping correlations Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space Data-Efficient Learning for Asymptotically Smooth Integral Operators
Optimal control	A Proximal Descent Method for Nonconvex Policy Optimization
Optimal transport	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
Optimization	What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty Informal and Privatized Transit: Incentives, Efficiency and Coordination
Optimization under Uncertainty	What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty
oracle estimators	Adaptive Minimax Estimation Across SNR Regimes
P
packet erasure	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
Parallel sampling	Faster Diffusion Language Models
Parallel transport	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
Pareto efficiency	Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback
partial observability	Online World Modeling for Closed-Loop Planning Under Partial Observability
Path Integral Diffusion	Path-Integral Diffusion: From Generative AI and Interacting Agents to Quantum Measurements
PCA	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
PDE	Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment.
Perfect Bayesian Equilibrium	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
Perfect Secrecy	Secret key-distribution over networks with node-based adversarial errors
Personalized Federated Learning	Eigenspace-Based Clustering for Personalized System Identification
perturbation stability	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
physical AI	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
physical layer security	A demonstration of information leakage via phase contamination
physical plausibility	Beyond Photorealism: 3D Reconstruction and Generation with Multimodal and Physical Grounding
physical-layer confidentiality	Improving Confidentiality in Wireless Networks with Non-Linear Relays and Deep-Learning
Pilot contamination	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework
planning	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
polar codes	Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy
Policy optimization	A Proximal Descent Method for Nonconvex Policy Optimization
Population games	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
posterior sampling	Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Power system stability and control	Determining and Improving Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment and Preventive Action
Power systems	A Graph Neural Network Foundation Model for AC Optimal Power Flow
power transfer distribution factors	A Single ML Model for Predicting AC Power Flow Solutions under Line Contingencies
precoding	Interpreting End-to-End Learned CSI Feedback for Massive MIMO
Preference Aggregation	Preference Aggregation in the Age of AI
Price of Anarchy	Informal and Privatized Transit: Incentives, Efficiency and Coordination
Principal-Agent Interactions	Optimal Incentive Contracting for Sensing and Searching for Rewards on a Graph
principle agent models	Career Concerns and Social Learning in Principal-Agent Environments
Private Information Retrieval	Revisiting SPIR-Based PSI: A Computational Perspective PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions
private selection	Differentially Private Selection using Enhanced Sensitivity Concepts
Private Set Intersection	Revisiting SPIR-Based PSI: A Computational Perspective
privileged information	The Information Needs of Robot Learners
probabilistic graphical models	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Prophet inequalities	Prophet Inequalities with Cancellation Costs
Q
Quantized control	On data-driven control of linear systems with quantized data
quantum key distribution
Quantum Measurements	Path-Integral Diffusion: From Generative AI and Interacting Agents to Quantum Measurements
Quantum state tomography	Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
quickest change detection	Sequential Change Detection with Differential Privacy
R
Random Access	Analysis and Optimization of Age of Information in Large-Scale Random Access Networks
randomized algorithm	Data-Efficient Learning for Asymptotically Smooth Integral Operators
rank adaptation	Rank-Adaptive Matrix-Free Atomic Quantum State Tomography
Rank Degeneracy	Fisher Simplicity in KANs and MLPs
rank statistics	Temporal Rank Statistics under Markov Dependence
Rare-events simulations	Fast operator learning for mapping correlations
Rate-Distortion	The Rate-Distortion-Deception Tradeoff
Rate-Distortion Theory	Few-Shot Universal Analog Communication
reconfigurable intelligent surface	Near-Field RIS-Assisted In-Cabin 3D Localization and Harmonic-Aware Vital Sign Estimation
Reconfigurable intelligent surfaces	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework
Reed-Muller codes	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Reed–Solomon codes	Constructing Reed–Solomon Codes with Sparse Parity Checks
Reinforcement learning	Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Unified Bellman-Operator Framework Constrained Dynamic Grasping under Limited Visual Feedback PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost On the Efficiency of GRPO and the Generalization of Diffusion Models
Reinforcement learning with verifiable rewards Hierarchical reinforcement learning	ECHO: Stackelberg Learning for Entropy Constrained Hierarchical Optimization in Tool Calling Agents
rejection sampling	Learnable Chernoff Baselines for Provable Inference-Time Alignment
reliable generation	Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics
remote monitoring	Remote IoT Source Monitoring with Delayed Feedback
Replicator equation	An ODE-based method for resource allocation in a multi-agent systems
Representation theory	On Controllability of Diffeomorphisms
reproducing kernel Hilbert space	Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space
reservoir computing	From Echo States to Dominant Manifolds: A Systems-Theoretic View of Reservoir Computing
Resource allocation	An ODE-based method for resource allocation in a multi-agent systems
Restless Multi-Arm Bandits	Load Balancing with Partial Queue Information: Threshold Optimality and Indexability
reverse dynamics	Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics
Riemannian Optimization	Frechet Regression on Curved Manifolds
RL	AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents
robot foundation models	Toward Compositional Generalization in the Physical World
Robot learning	Learning to Design Robots The Information Needs of Robot Learners
Robotics	Learning to Design Robots
Robust LASSO	Operator-Norm Robust LASSO: A Precise Analysis and an AMP-style Algorithm
Robust Optimization	Reconfiguration and Real-Time Control of Networked Microgrids Under Load Uncertainty
robust statistics	Robust and Adversarial Sequential Change-Point Detection in High Dimensions
roots of unity	Observability conditions for neural state-space models with eigenvalues and their roots of unity
S
Safe Learning	Regret-Optimal Safe Adaptive Control under Chance Constraints: Application to Thermostatically Controlled Loads
safety	Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond
sample complexity	Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
Sampling	Feedback Based Sampling using L2 Gradient Flows Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond Mean-shift interacting particle systems for sampling and quantization
scheduling
Schrödinger Bridge	Nonlinearity and Interaction in Schrödinger Bridges
Score-Based Classification	When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?
score-based generative models	Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo
Secondary Control
secure computation	PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions
security and trust	Verifiably Safe Decentralized Control via Event-Triggered Topology Switching
Self-attention dynamics	Localmax Dynamics for Attention Models
semantic communication	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
Sequential change-point detection	Robust and Adversarial Sequential Change-Point Detection in High Dimensions
side information	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Signal Processing	Eigenspace-Based Clustering for Personalized System Identification
signal recovery	Improved Convex Relaxations for Simultaneously Sparse and Quantized Signal recovery
signal-to-noise ratio	Adaptive Minimax Estimation Across SNR Regimes
Signaling Games	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
Signature	From Sequence to Signature: Infinite-Order Signature Kernels for Biological Sequence Learning
sim-to-real	Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
simulated annealing	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
Sinkhorn algorithm	Nonlinearity and Interaction in Schrödinger Bridges
small datasets	Cross-Validation Error Dynamics in Smaller Datasets
smooth sensitivity	Differentially Private Selection using Enhanced Sensitivity Concepts
Social Choice	Preference Aggregation in the Age of AI
social learning	Career Concerns and Social Learning in Principal-Agent Environments
social learning from reviews	Optimal Exploration of New Products under Assortment Decisions
Socio-Technical Systems	Learning to Coordinate over Networks with Heterogeneous Rationalities
soft-decision decoding
source separation	Source-Reliability Weighted Observer Design for Open Client–Server Networks
sparse parity-check matrices	Constructing Reed–Solomon Codes with Sparse Parity Checks
sparsity	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model Adaptive Minimax Estimation Across SNR Regimes
spatial reasoning	Online World Modeling for Closed-Loop Planning Under Partial Observability
Spectral Methods	Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment.
Spectral optimization	Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks
spline neural networks	Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
Stackelberg games	ECHO: Stackelberg Learning for Entropy Constrained Hierarchical Optimization in Tool Calling Agents
state estimation	Source-Reliability Weighted Observer Design for Open Client–Server Networks
state-space models	Observability conditions for neural state-space models with eigenvalues and their roots of unity
Steering
Stein's Method	Efficient Concentration through Stein's Method: An Illustration in Abandonment Queues
Stochastic control	Reasoning and learning to play against passive and reactive agents Nonlinearity and Interaction in Schrödinger Bridges
Stochastic games	Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback
Stochastic Geometry	Stochastic Geometry meets Optimization: Soft Deployment in Cellular Networks
Stochastic Optimization	Stochastic Geometry meets Optimization: Soft Deployment in Cellular Networks Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization High Probability Bounds for Stochastic Optimization Algorithms
Storage functions	Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations
Strassen's theorem	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
Strategic Communication	The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap
Strategic complementarities	ECHO: Stackelberg Learning for Entropy Constrained Hierarchical Optimization in Tool Calling Agents
strategic robustness	Strategically Robust Dynamic Games
strong data processing inequality	Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model
structure learning	Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Structured preconditioning	Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization
stuck cells	Reed-Muller Codes for Joint Random and Stuck-At Error Correction
Subspace methods	Trusting and Adapting Data-Driven Predictors for Control
support constraints	Constructing Reed–Solomon Codes with Sparse Parity Checks
symmetrization	Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings
Synthetic Data Augmentation	When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?
System Identification	Eigenspace-Based Clustering for Personalized System Identification
T
tail-sensitive	Tail-Aware Bandits: Optimal Rules and Algorithm
temporal ranks	Temporal Rank Statistics under Markov Dependence
Thermostatically Controlled Loads	Regret-Optimal Safe Adaptive Control under Chance Constraints: Application to Thermostatically Controlled Loads
time series forecasting	From Echo States to Dominant Manifolds: A Systems-Theoretic View of Reservoir Computing
Tool-calling agents	ECHO: Stackelberg Learning for Entropy Constrained Hierarchical Optimization in Tool Calling Agents
total variation distance	Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles
Transformers	Localmax Dynamics for Attention Models
Transition path theory	Fast operator learning for mapping correlations
transmitter contamination	A demonstration of information leakage via phase contamination
Transportation of measure	Mean-shift interacting particle systems for sampling and quantization
Transportation Systems	On the Necessity of Pricing to Steer Nonatomic No-Regret Agents to a Desired Bayes Correlated Equilibrium
tree correlation tests	Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
U
Uncertain Loads	Reconfiguration and Real-Time Control of Networked Microgrids Under Load Uncertainty
Uncertainty	What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty
Uncertainty quantification	Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
unequal error protection	Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
Unit commitment	Copositive characterization of convex hull pricing
urban monitoring	Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing
User-centric cell-free massive MIMO	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework
V
Vector approximation	Compromising Offline RLHF: An Efficient Preference Poisoning Approach
video generation	Are Normalizing Flows Good Candidates for Interactive World Models?
vision-language-action models	Toward Compositional Generalization in the Physical World
Visual servoing	Constrained Dynamic Grasping under Limited Visual Feedback
von Neumann algebras	Affiliated operators for classical and quantum control
Vulnerability assessment and preventive action	Determining and Improving Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment and Preventive Action
W
Wasserstein	Efficient Concentration through Stein's Method: An Illustration in Abandonment Queues
Wasserstein barycenter	Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
Wasserstein distance	Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains
watermarking	In-Context Watermarks for Large Language Models
weighted least squares	Source-Reliability Weighted Observer Design for Open Client–Server Networks
Whittle indexability	Load Balancing with Partial Queue Information: Threshold Optimality and Indexability
Wireless communication systems	Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework
Wireless Networks	Analysis and Optimization of Age of Information in Large-Scale Random Access Networks
world model	Online World Modeling for Closed-Loop Planning Under Partial Observability
world models	Are Normalizing Flows Good Candidates for Interactive World Models? Toward Compositional Generalization in the Physical World

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