Murphy, Susan

14 publications

AISTATS 2025 Harnessing Causality in Reinforcement Learning with Bagged Decision Times Daiqi Gao, Hsin-Yu Lai, Predrag Klasnja, Susan Murphy

NeurIPSW 2024 BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings Karine Karine, Susan Murphy, Benjamin Marlin

AISTATS 2024 Contextual Bandits with Budgeted Information Reveal Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan Murphy

JMLR 2024 Effect-Invariant Mechanisms for Policy Generalization Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters

AISTATS 2024 Online Learning in Bandits with Predicted Context Yongyi Guo, Ziping Xu, Susan Murphy

NeurIPSW 2023 Causality in Goal Conditioned RL: Return to No Future? Ivana Malenica, Susan Murphy

TMLR 2023 Online Model Selection by Learning How Compositional Kernels Evolve Eura Shin, Predrag Klasnja, Susan Murphy, Finale Doshi-Velez

ICML 2023 The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan Murphy, Finale Doshi-Velez

MLHC 2021 Power Constrained Bandits Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-Velez

NeurIPS 2021 Statistical Inference with M-Estimators on Adaptively Collected Data Kelly Zhang, Lucas Janson, Susan Murphy

NeurIPS 2020 Inference for Batched Bandits Kelly Zhang, Lucas Janson, Susan Murphy

ICMLW 2019 Intelligent Pooling in Thompson Sampling for Rapid Personalization in Mobile Health Sabina Tomkins, Peng Liao, Serena Yeung, Predrag Klasnja, Susan Murphy

NeurIPS 2017 Action Centered Contextual Bandits Kristjan Greenewald, Ambuj Tewari, Susan Murphy, Predag Klasnja

AISTATS 2010 Model-Free Monte Carlo-like Policy Evaluation Raphael Fonteneau, Susan Murphy, Louis Wehenkel, Damien Ernst