Andrew Perrault
Preprints
Reinforcement Learning for Fine-tuning Text-to-speech Diffusion Models
Jingyi Chen, Ju-Seung Byun, Micha Elsner and Andrew Perrault.Normality-Guided Distributional Reinforcement Learning for Continuous Control
Ju-Seung Byun and Andrew Perrault.Publications
Using RLHF to align speech enhancement approaches to mean-opinion quality scores
Anurag Kumar, Andrew Perrault, and Donald S. Williamson. ICASSP 2025.The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards
Xi Chen, Zhihui Zhu and Andrew Perrault. AAAI 2025.Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution
Adam Zychowski, Andrew Perrault, Jacek Mandziuk. AAAI 2025.ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback
Ju-Seung Byun, Jiyun Chun, Jihyung Kil, and Andrew Perrault. EMNLP (main) 2024.On-farm cereal rye biomass estimation using machine learning on images from an unmanned aerial system
Kushal KC, Matthew Romanko, Andrew Perrault and Sami Khanal. Precision Agriculture, 2024.Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling (short paper)
Yi Mao and Andrew Perrault. AAMAS 2024.Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling
Yi Mao and Andrew Perrault. 5th International Workshop on Autonomous Agents for Social Good (AASG) 2024.Multi-Objective Multi-Cluster Optimization of Non-Pharmaceutical Interventions for Infectious Disease With Resource Constraints
Xueqiao Peng, Yi Mao, Xi Chen, Dinh Song An Nguyen, Andrew Perrault. 5th International Workshop on Autonomous Agents for Social Good (AASG) 2024.Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe. AAAI 2024.Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret
Adam Zychowski, Andrew Perrault, Jacek Mandziuk. AAAI 2024.Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease
Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault. ML4H 2023 (supersedes epiDAMIK version below).Bootstrapping a Conversational Guide for Colonoscopy Prep
Pulkit Arya, Madeleine Bloomquist, Subhankar Chakraborty, Andrew Perrault, William Schuler, Eric Fosler-Lussier, Michael White. SIGDIAL 2023.Using Reinforcement Learning for Multi-Objective Cluster-Level NPI Optimization
Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault. epiDAMIK Workshop at KDD 2023.Risk-Based Ring Vaccination: A Strategy for Pandemic Control and Vaccine Allocation
Dinh Song An Nguyen, Marie-Laure Charpignon, Kathryn L Schaber, Maimuna S. Majumder, Andrew Perrault. epiDAMIK Workshop at KDD 2023.Data Collection, Management, Analysis and Decision Support During COVID-19: A Retrospective from The Ohio State University
Namrata Banerji, Steve Chang, Andrew Perrault, Tanya Berger-Wolf, Mikkel Quam. epiDAMIK Workshop at KDD 2023.Reflections from the Workshop on AI-Assisted Decision Making for Conservation
Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe.Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses
Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe. NeurIPS 2022.Open Problems in (Un)fairness of the Retail Food Safety Inspection Process
Tanya Berger-Wolf, Allison Howell, Chris Kanich, Ian A. Kash, Moniba Keymanesh, Barbara Kowalcyk, Gina Nicholson Kramer, Andrew Perrault, Shubham Singh. ICML 2022 Workshop on Responsible Decision Making in Dynamic Environments.Training Transition Policies via Distribution Matching for Complex Tasks
Ju-Seung Byun and Andrew Perrault. ICLR 2022.Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games
Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, and Milind Tambe. AAAI 2022.Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe. NeurIPS 2021 (spotlight).Robust Reinforcement Learning Under Minimax Regret for Green Security
Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe. UAI 2021.Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits
Aditya Mate, Andrew Perrault, and Milind Tambe. AAMAS 2021.Beyond “To Act or Not to Act”: Fast Lagrangian Approaches to General Multi-Action Restless Bandits
Jackson Killian, Andrew Perrault, and Milind Tambe. AAMAS 2021.Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and Milind Tambe. AAAI 2021.AAAI Best paper runner-up.
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline
Andrew Perrault, Fei Fang, Arunesh Sinha, and Milind Tambe. AI Magazine, Winter 2020.Collapsing Bandits and Their Application to Public Health Interventions
Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, and Milind Tambe. NeurIPS 2020.Automatically Learning Compact Quality-aware Surrogates for Optimization Problems
Kai Wang, Bryan Wilder, Andrew Perrault, and Milind Tambe. NeurIPS 2020 (spotlight).Designing Efficient Contact Tracing Through Risk-Based Quarantining
Andrew Perrault, Marie Charpignon, Jonathan Gruber, Milind Tambe, and Maimuna S. Majumder. medRxiv and NBER.Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
Bryan Wilder, Marie Charpignon, Jackson A. Killian, Han-Ching Ou, Aditya Mate, Shahin Jabbari, Andrew Perrault, Angel Desai, Milind Tambe and Maimuna S. Majumder. PNAS, 2020.Robust Spatial-Temporal Incident Prediction
Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, and Yevgeniy Vorobeychik. UAI 2020.Optimization of the Low-Carbon Energy Transition Under Static and Adaptive Carbon Taxes via Markov Decision Processes
Alaisha Sharma, Jackson Killian and Andrew Perrault. CRCS AI for Social Good Workshop 2020.Influence Maximization and Equilibrium Strategies in Election Network Games
Anya Zhang and Andrew Perrault. CRCS AI for Social Good Workshop 2020.Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty
Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, and Milind Tambe. AAMAS 2020.Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games
Kai Wang, Andrew Perrault, Aditya Mate and Milind Tambe. AAMAS 2020.Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, and Milind Tambe. AAAI 2020.End-to-End Game-Focused Learning of Adversary Behavior in Security Games
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina and Milind Tambe. AAAI 2020.Experiential Preference Elicitation for Autonomous Heating and Cooling Systems
Andrew Perrault and Craig Boutilier. AAMAS 2019.Developing and Coordinating Autonomous Agents for Efficient Electricity Markets
Andrew Perrault and Craig Boutilier. 2018 (PhD thesis).Multiple-Profile Prediction-of-Use Games
Andrew Perrault and Craig Boutilier. IJCAI 2017.Best workshop paper, CoopMAS workshop.