Bennett, Andrew

11 publications

NeurIPS 2024 Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes Andrew Bennett, Nathan Kallus, Miruna Oprescu, Wen Sun, Kaiwen Wang

AISTATS 2024 Low-Rank MDPs with Continuous Action Spaces Miruna Oprescu, Andrew Bennett, Nathan Kallus

ICLR 2024 VQ-TR: Vector Quantized Attention for Time Series Forecasting Kashif Rasul, Andrew Bennett, Pablo Vicente, Umang Gupta, Hena Ghonia, Anderson Schneider, Yuriy Nevmyvaka

NeurIPS 2023 Future-Dependent Value-Based Off-Policy Evaluation in POMDPs Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun

COLT 2023 Inference on Strongly Identified Functionals of Weakly Identified Functions Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara

COLT 2023 Minimax Instrumental Variable Regression and $l_2$ Convergence Guarantees Without Identification or Closedness Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara

AISTATS 2023 Provable Safe Reinforcement Learning with Binary Feedback Andrew Bennett, Dipendra Misra, Nathan Kallus

AISTATS 2021 Off-Policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi

ICML 2020 Efficient Policy Learning from Surrogate-Loss Classification Reductions Andrew Bennett, Nathan Kallus

NeurIPS 2019 Deep Generalized Method of Moments for Instrumental Variable Analysis Andrew Bennett, Nathan Kallus, Tobias Schnabel

NeurIPS 2019 Policy Evaluation with Latent Confounders via Optimal Balance Andrew Bennett, Nathan Kallus