Andrew Perrault

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 51

Top Topics

Infectious Disease

Reinforcement Learning

Coevolutionary Algorithm

Top Venues

Publications

Adam Zychowski, Andrew Perrault, Jacek Mandziuk
Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret. AAAI (2024)
Ju-Seung Byun, Andrew Perrault
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales. CoRR (2024)
Yi Mao, Andrew Perrault
Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling. AAMAS (2024)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. AAAI (2024)
Xi Chen, Zhihui Zhu, Andrew Perrault
The Distributional Reward Critic Architecture for Perturbed-Reward Reinforcement Learning. CoRR (2024)
Jingyi Chen, Ju-Seung Byun, Micha Elsner, Andrew Perrault
Reinforcement Learning for Fine-tuning Text-to-speech Diffusion Models. CoRR (2024)
Ju-Seung Byun, Jiyun Chun, Jihyung Kil, Andrew Perrault
ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback. CoRR (2024)
Adam Zychowski, Andrew Perrault, Jacek Mandziuk
Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret. CoRR (2023)
Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize. CoRR (2023)
Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault
Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease. ML4H@NeurIPS (2023)
Andrew Perrault
Monitoring and Intervening on Large Populations of Weakly Coupled Processes with Social Impact Applications. AAAI (2023)
Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. 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
Reflections from the Workshop on AI-Assisted Decision Making for Conservation. CoRR (2023)
Pulkit Arya, Madeleine Bloomquist, Subhankar Chakraborty, Andrew Perrault, William Schuler, Eric Fosler-Lussier, Michael White
Bootstrapping a Conversational Guide for Colonoscopy Prep. SIGDIAL (2023)
Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. NeurIPS (2022)
Ju-Seung Byun, Andrew Perrault
Normality-Guided Distributional Reinforcement Learning for Continuous Control. CoRR (2022)
Ju-Seung Byun, Andrew Perrault
Training Transition Policies via Distribution Matching for Complex Tasks. ICLR (2022)
Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games. AAAI (2022)
Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR (2022)
Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. AAAI (2021)
Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
Robust Reinforcement Learning Under Minimax Regret for Green Security. CoRR (2021)
Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe
Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games. CoRR (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning. CoRR (2021)
Aditya Mate, Andrew Perrault, Milind Tambe
Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. AAMAS (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning. NeurIPS (2021)
Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
Robust reinforcement learning under minimax regret for green security. UAI (2021)
Jackson A. Killian, Andrew Perrault, Milind Tambe
Beyond "To Act or Not to Act": Fast Lagrangian Approaches to General Multi-Action Restless Bandits. AAMAS (2021)
Ju-Seung Byun, Andrew Perrault
Training Transition Policies via Distribution Matching for Complex Tasks. CoRR (2021)
Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe
Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games. AAMAS (2020)
Lily Xu, Andrew Perrault, Andrew J. Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Milind Tambe
Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers. CoRR (2020)
Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe
Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Mag. 41 (4) (2020)
Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik
Robust Spatial-Temporal Incident Prediction. UAI (2020)
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI (2020)
Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe
Collapsing Bandits and Their Application to Public Health Interventions. CoRR (2020)
Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty. AAMAS (2020)
Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. CoRR (2020)
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
End-to-End Game-Focused Learning of Adversary Behavior in Security Games. AAAI (2020)
Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. CoRR (2020)
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. NeurIPS (2020)
Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. CoRR (2020)
Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe
Collapsing Bandits and Their Application to Public Health Intervention. NeurIPS (2020)
Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. CoRR (2019)
Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe
Decision-Focused Learning of Adversary Behavior in Security Games. CoRR (2019)
Andrew Perrault, Craig Boutilier
Experiential Preference Elicitation for Autonomous Heating and Cooling Systems. AAMAS (2019)
Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Milind Tambe
Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty. CoRR (2019)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. IJCAI (2017)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. AAMAS Workshops (Selected Papers) (2017)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. AAMAS (2017)
Andrew Perrault, Joanna Drummond, Fahiem Bacchus
Strategy-Proofness in the Stable Matching Problem with Couples. AAMAS (2016)
Joanna Drummond, Andrew Perrault, Fahiem Bacchus
SAT Is an Effective and Complete Method for Solving Stable Matching Problems with Couples. IJCAI (2015)
Andrew Perrault, Craig Boutilier
Approximately Stable Pricing for Coordinated Purchasing of Electricity. IJCAI (2015)
Andrew Perrault, Joanna Drummond, Fahiem Bacchus
Exploring Strategy-Proofness, Uniqueness, and Pareto Optimality for the Stable Matching Problem with Couples. CoRR (2015)
Andrew Perrault, Craig Boutilier
Efficient coordinated power distribution on private infrastructure. AAMAS (2014)