Energy-Efficient RIS-Assisted User-Centric Cell-Free Massive MIMO: A Game-Theoretic Framework (abstract)

Source-Reliability Weighted Observer Design for Open Client–Server Networks (abstract)

Information-Theoretic Bounds for Sparse Covariance Estimation in the Vertical-Split Distributed Model (abstract)

Remote IoT Source Monitoring with Delayed Feedback (abstract)

Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission (abstract)

Tail-Aware Bandits: Optimal Rules and Algorithm (abstract)

Sequential Change Detection with Differential Privacy (abstract)

Robust and Adversarial Sequential Change-Point Detection in High Dimensions (abstract)

Convergence of Fictitious Play in a Class of Product Markov Games (abstract)

On the Necessity of Pricing to Steer Nonatomic No-Regret Agents to a Desired Bayes Correlated Equilibrium (abstract)

Strategically Robust Dynamic Games (abstract)

The robustness of games as models in multi-agent control: studying stability and sensitivity to misspecification (abstract)

Learning to Avoid Tragedies: Feedback-Evolving Games with Heterogeneous Learning Rules (abstract)

On the Efficiency of GRPO and the Generalization of Diffusion Models (abstract)

Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning (abstract)

Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning (abstract)

Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo (abstract)

Fast operator learning for mapping correlations (abstract)

Test-Time Anchoring for Discrete Diffusion Posterior Sampling (abstract)

Local and Global Approaches to Kernelized Bandit Optimization (abstract)

Quantifying Classification Performance using Combinatorial Geometry and Local Data Analysis (abstract)

Distributed 20 Questions for Classification (abstract)

Adversarially Robust Multiclass Classification via Error Correction Output Codes (abstract)

Cross-Validation Error Dynamics in Smaller Datasets (abstract)

Information Lattice Learning as Probabilistic Graphical Model Structure Learning (abstract)

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification? (abstract)

Kullback-Leibler Divergence Regularized Learning (KLD-RL) Dynamics in Population Games (abstract)

Learning to Coordinate over Networks with Heterogeneous Rationalities (abstract)

Counterclockwise Dissipativity and Lyapunov Stability in Learning for Large Populations (abstract)

Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback (abstract)

Fictitious Play in Extensive-Form Games of Imperfect Information (abstract)

Few-Shot Universal Analog Communication (abstract)

Impact of State Knowledge on Covert Communication in the Presence of Simultaneous Transmission (abstract)

Improving Confidentiality in Wireless Networks with Non-Linear Relays and Deep-Learning (abstract)

The Rate-Distortion-Deception Tradeoff (abstract)

Stochastic Geometry meets Optimization: Soft Deployment in Cellular Networks (abstract)

Determining and Improving Safety Margins of Parameterized Nonlinear Systems for Vulnerability Assessment and Preventive Action (abstract)

Copositive characterization of convex hull pricing (abstract)

Low-Rank and Lifted Semidefinite Programming for Global MINLP Power Grid Optimization (abstract)

A Single ML Model for Predicting AC Power Flow Solutions under Line Contingencies (abstract)

Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests (abstract)

Load Balancing with Partial Queue Information: Threshold Optimality and Indexability (abstract)

Temporal Rank Statistics under Markov Dependence (abstract)

Operator-Norm Robust LASSO: A Precise Analysis and an AMP-style Algorithm (abstract)

Improved Convex Relaxations for Simultaneously Sparse and Quantized Signal recovery (abstract)

Adaptive Minimax Estimation Across SNR Regimes (abstract)

Rank-Adaptive Matrix-Free Atomic Quantum State Tomography (abstract)

Low-Temperature Sensitivity and Perturbation Stability of Annealed Markov-Chain Ensembles (abstract)

Adaptive Decentralized Learning in Adversary-Dominated Settings (abstract)

Embodied Persuasion: Information Design and Physical Leakage in Markov Games (abstract)

Adaptive Decentralized Optimization (abstract)

Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization (abstract)

Behavioral System Theory for Dynamic Optimization (abstract)

Data-Efficient Learning for Asymptotically Smooth Integral Operators (abstract)

Trusting and Adapting Data-Driven Predictors for Control (abstract)

Limitations and capabilities of autoencoders for learning dynamics (abstract)

Affiliated operators for classical and quantum control (abstract)

Koopman Modeling and Stabilization of Discrete-Time Nonlinear Control Systems: Bilinearity on a Reproducing Kernel Hilbert Space (abstract)

Informal and Privatized Transit: Incentives, Efficiency and Coordination (abstract)

Water-filling is Universally Minimax Optimal (abstract)

Preference Aggregation in the Age of AI (abstract)

What Data Enables Optimal Decisions? A Study of Data Informativeness in Optimization Under Uncertainty (abstract)

An ODE-based method for resource allocation in a multi-agent systems (abstract)

Prophet Inequalities with Cancellation Costs (abstract)

Efficient Concentration through Stein's Method: An Illustration in Abandonment Queues (abstract)

Frechet Regression on Curved Manifolds (abstract)

Localmax Dynamics for Attention Models (abstract)

High Probability Bounds for Stochastic Optimization Algorithms (abstract)

Verifiably Safe Decentralized Control via Event-Triggered Topology Switching (abstract)

In-Context Watermarks for Large Language Models (abstract)

Minimizing Convex Risk in Data Fusion via Symmetrization and Martingale Couplings (abstract)

Compromising Offline RLHF: An Efficient Preference Poisoning Approach (abstract)

Beyond Photorealism: 3D Reconstruction and Generation with Multimodal and Physical Grounding (abstract)

Online World Modeling for Closed-Loop Planning Under Partial Observability (abstract)

Are Normalizing Flows Good Candidates for Interactive World Models? (abstract)

Toward Compositional Generalization in the Physical World (abstract)

Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics (abstract)

ECHO: Stackelberg Learning for Entropy Constrained Hierarchical Optimization in Tool Calling Agents (abstract)

Faster Diffusion Language Models (abstract)

Constructing Reed–Solomon Codes with Sparse Parity Checks (abstract)

Reed-Muller Codes for Joint Random and Stuck-At Error Correction (abstract)

Secret key-distribution over networks with node-based adversarial errors (abstract)

Enhanced Feedback Mechanisms for Resource-Efficient Incremental Redundancy (abstract)

Universal Parameter-Free First-Order Algorithms for Convex Optimization (abstract)

Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence (abstract)

Reasoning and learning to play against passive and reactive agents (abstract)

Career Concerns and Social Learning in Principal-Agent Environments (abstract)

Optimal Incentive Contracting for Sensing and Searching for Rewards on a Graph (abstract)

The Price of Transparency in Information Design: Bayesian Persuasion, Signaling, and the Commitment Gap (abstract)

PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost (abstract)

Learnable Chernoff Baselines for Provable Inference-Time Alignment (abstract)

Reconfiguration and Real-Time Control of Networked Microgrids Under Load Uncertainty (abstract)

A Graph Neural Network Foundation Model for AC Optimal Power Flow (abstract)

Regret-Optimal Safe Adaptive Control under Chance Constraints: Application to Thermostatically Controlled Loads (abstract)

Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment. (abstract)

Fisher Simplicity in KANs and MLPs (abstract)

Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks (abstract)

Observability conditions for neural state-space models with eigenvalues and their roots of unity (abstract)

From Sequence to Signature: Infinite-Order Signature Kernels for Biological Sequence Learning (abstract)

Deep Reinforcement Learning for MSense: Learned Destroy–Repair Policies for Diversity-Aware and Heterogeneous Mobile Sensor Routing (abstract)

On data-driven control of linear systems with quantized data (abstract)

From Echo States to Dominant Manifolds: A Systems-Theoretic View of Reservoir Computing (abstract)

On Controllability of Diffeomorphisms (abstract)

A Proximal Descent Method for Nonconvex Policy Optimization (abstract)

On the Inductive Bias for Learning in Nonlinear Control: Trade-offs and Guarantees (abstract)

Constrained Dynamic Grasping under Limited Visual Feedback (abstract)

AI-Native Open RAN: A Roadmap from xApps and rApps to Autonomous Network Agents (abstract)

$\alpha$-Mutual Information for the Gaussian Noise Channel (abstract)

Interpreting End-to-End Learned CSI Feedback for Massive MIMO (abstract)

Near-Field RIS-Assisted In-Cabin 3D Localization and Harmonic-Aware Vital Sign Estimation (abstract)

A demonstration of information leakage via phase contamination (abstract)

Analysis and Optimization of Age of Information in Large-Scale Random Access Networks (abstract)

Mean-shift interacting particle systems for sampling and quantization (abstract)

Feedback Based Sampling using L2 Gradient Flows (abstract)

Path-Integral Diffusion: From Generative AI and Interacting Agents to Quantum Measurements (abstract)

Nonlinearity and Interaction in Schrödinger Bridges (abstract)

Hard-Constrained Sampling in Diffusion and Flow-Matching Models for Safe Control and Beyond (abstract)

Wasserstein‑$p$ Central Limit Theorem Rates: From Local Dependence to Markov Chains (abstract)

Optimal Exploration of New Products under Assortment Decisions (abstract)

Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Unified Bellman-Operator Framework (abstract)

Modulated learning for private and distributed regression with just a single sample per client device (abstract)

Communication-Efficient Random Spectral Descent for Federated Learning over Noisy Networks (abstract)

Budget-Constrained Multi-Consensus Decentralized Gradient Descent (abstract)

Eigenspace-Based Clustering for Personalized System Identification (abstract)

Revisiting SPIR-Based PSI: A Computational Perspective (abstract)

Differentially Private Selection using Enhanced Sensitivity Concepts (abstract)

PIR-DAG: Information-Theoretic Private Evaluation of Boolean Functions (abstract)

The Information Needs of Robot Learners (abstract)

Learning to Design Robots (abstract)