Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency

Many Preferences, Few Policies: Towards Scalable Language Model Personalization

Learning Provably Correct Distributed Protocols Without Human Knowledge

Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization

Optimizing Resource-Constrained Non-Pharmaceutical Interventions for Multi-Cluster Outbreak Control Using Hierarchical Reinforcement Learning

Spatiotemporal Modeling of the Substance Overdose Epidemic in the United States Using Time-Series Clustering

VISTA Score: Verification In Sequential Turn-based Assessment

Evaluating Large Language Models for Colonoscopy Preparation Assistance: Correctness and Diversity in Synthetic Dialogues

Pacing with ROI: Budget Allocation in Sponsored Search

Do Audio LLMs Really LISTEN, or Just Transcribe? Measuring Lexical vs. Acoustic Emotion Cues Reliance

Beyond Length: Context-Aware Expansion and Independence as Developmentally Sensitive Evaluation in Child Utterances

Optimizing Urban Service Allocation with Time-Constrained Restless Bandits

Machine Learning-Accelerated Calibration of Complex Heat Source Models for Welding and Additive Manufacturing Process Simulation

Fine-Tuning Text-to-Speech Diffusion Models Using Reinforcement Learning with Human Feedback

Understanding Learned Representations and Action Collapse in Visual Reinforcement Learning

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales

The Next Wave of AI for Social Impact: Challenges and Opportunities

Normality-Guided Distributional Reinforcement Learning for Continuous Control

Using RLHF to align speech enhancement approaches to mean-opinion quality scores

The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards

Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution

ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback

On-farm cereal rye biomass estimation using machine learning on images from an unmanned aerial system

Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling (short paper)

Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling

Multi-Objective Multi-Cluster Optimization of Non-Pharmaceutical Interventions for Infectious Disease With Resource Constraints

Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize

Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret

Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease

Bootstrapping a Conversational Guide for Colonoscopy Prep

Using Reinforcement Learning for Multi-Objective Cluster-Level NPI Optimization

Risk-Based Ring Vaccination: A Strategy for Pandemic Control and Vaccine Allocation

Pandemic Data Collection, Management, Analysis and Decision Support: A Large Urban University Retrospective

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses

Open Problems in (Un)fairness of the Retail Food Safety Inspection Process

Training Transition Policies via Distribution Matching for Complex Tasks

Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning

Robust Reinforcement Learning Under Minimax Regret for Green Security

Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits

Beyond “To Act or Not to Act”: Fast Lagrangian Approaches to General Multi-Action Restless Bandits

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security

AAAI Best paper runner-up.

AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline

Collapsing Bandits and Their Application to Public Health Interventions

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

Designing Efficient Contact Tracing Through Risk-Based Quarantining

Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City

Robust Spatial-Temporal Incident Prediction

Optimization of the Low-Carbon Energy Transition Under Static and Adaptive Carbon Taxes via Markov Decision Processes

Influence Maximization and Equilibrium Strategies in Election Network Games

Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty

Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games

Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning

End-to-End Game-Focused Learning of Adversary Behavior in Security Games

Experiential Preference Elicitation for Autonomous Heating and Cooling Systems

Developing and Coordinating Autonomous Agents for Efficient Electricity Markets

Multiple-Profile Prediction-of-Use Games

Best workshop paper, CoopMAS workshop.

Strategy-Proofness in the Stable Matching Problem with Couples

Approximately Stable Pricing for Coordinated Purchasing of Electricity

SAT is an Effective and Complete Method for Solving Stable Matching Problems with Couples

Efficient Coordinated Power Distribution on Private Infrastructure

Efficient Coordinated Power Distribution on Private Infrastructure

Polynomial Time Construction for Spatially Balanced Latin Squares