Gottesman, Omer

18 publications

ICLR 2025 Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces Saket Tiwari, Omer Gottesman, George Konidaris

MLHC 2024 Decision-Focused Model-Based Reinforcement Learning for Reward Transfer Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez

NeurIPS 2024 Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael L. Littman, George Konidaris

ICMLW 2024 Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy Cameron Allen, Aaron T. Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael Littman, George Konidaris

AISTATS 2023 Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael Littman

NeurIPS 2023 Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning Akhil Bagaria, Ben Abbatematteo, Omer Gottesman, Matt Corsaro, Sreehari Rammohan, George Konidaris

ICLR 2023 Performance Bounds for Model and Policy Transfer in Hidden-Parameter MDPs Haotian Fu, Jiayu Yao, Omer Gottesman, Finale Doshi-Velez, George Konidaris

NeurIPS 2023 TD Convergence: An Optimization Perspective Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor

NeurIPS 2022 Faster Deep Reinforcement Learning with Slower Online Network Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J Smola

CHIL 2022 Identification of Subgroups with Similar Benefits in Off-Policy Policy Evaluation Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill

AAAI 2022 Optimistic Initialization for Exploration in Continuous Control Sam Lobel, Omer Gottesman, Cameron Allen, Akhil Bagaria, George Konidaris

NeurIPS 2021 Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris

ICML 2021 State Relevance for Off-Policy Evaluation Simon P Shen, Yecheng Ma, Omer Gottesman, Finale Doshi-Velez

ICML 2020 Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Celi, Emma Brunskill, Finale Doshi-Velez

NeurIPS 2020 Learning to Search Efficiently for Causally Near-Optimal Treatments Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D Johansson

ICML 2019 Combining Parametric and Nonparametric Models for Off-Policy Evaluation Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez

NeurIPS 2018 Representation Balancing MDPs for Off-Policy Policy Evaluation Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A Faisal, Finale Doshi-Velez, Emma Brunskill

AISTATS 2018 Weighted Tensor Decomposition for Learning Latent Variables with Partial Data Omer Gottesman, Weiwei Pan, Finale Doshi-Velez