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Publication search results
found 50 matches
- 2024
- Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe:
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize. AAAI 2024: 14902-14909 - Adam Zychowski, Andrew Perrault, Jacek Mandziuk:
Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret. AAAI 2024: 21869-21877 - Yi Mao, Andrew Perrault:
Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling. AAMAS 2024: 2375-2377 - Xi Chen, Zhihui Zhu, Andrew Perrault:
The Distributional Reward Critic Architecture for Perturbed-Reward Reinforcement Learning. CoRR abs/2401.05710 (2024) - 2023
- Andrew Perrault:
Monitoring and Intervening on Large Populations of Weakly Coupled Processes with Social Impact Applications. AAAI 2023: 15450 - 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: 445-460 - Pulkit Arya, Madeleine Bloomquist, Subhankar Chakraborty, Andrew Perrault, William Schuler, Eric Fosler-Lussier, Michael White:
Bootstrapping a Conversational Guide for Colonoscopy Prep. SIGDIAL 2023: 413-420 - Sanket Shah, Andrew Perrault, Bryan Wilder, Milind Tambe:
Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize. CoRR abs/2305.16830 (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 abs/2307.08774 (2023) - Adam Zychowski, Andrew Perrault, Jacek Mandziuk:
Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret. CoRR abs/2312.09078 (2023) - 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: 5219-5227 - Ju-Seung Byun, Andrew Perrault:
Training Transition Policies via Distribution Matching for Complex Tasks. ICLR 2022 - Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. NeurIPS 2022 - Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe:
Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems. CoRR abs/2203.16067 (2022) - Ju-Seung Byun, Andrew Perrault:
Normality-Guided Distributional Reinforcement Learning for Continuous Control. CoRR abs/2208.13125 (2022) - 2021
- Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe:
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. AAAI 2021: 14974-14982 - 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: 710-718 - Aditya Mate, Andrew Perrault, Milind Tambe:
Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits. AAMAS 2021: 880-888 - 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: 8795-8806 - Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust reinforcement learning under minimax regret for green security. UAI 2021: 257-267 - 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 abs/2106.03278 (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 abs/2106.03279 (2021) - Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust Reinforcement Learning Under Minimax Regret for Green Security. CoRR abs/2106.08413 (2021) - Ju-Seung Byun, Andrew Perrault:
Training Transition Policies via Distribution Matching for Complex Tasks. CoRR abs/2110.04357 (2021) - 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): 3-16 (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: 1378-1386 - Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI 2020: 2226-2235 - 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: 992-1000 - Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe:
Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games. AAMAS 2020: 1449-1457 - Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe:
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems. NeurIPS 2020
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