Omer Gottesman

According to our database, Omer Gottesman authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

CoRR, 2024

2023

iCVS - Inferring Cardio-Vascular hidden States from physiological signals available at the bedside.

Neta Ravid Tannenbaum, Omer Gottesman, Azadeh Assadi, Mjaye Mazwi, Uri Shalit, Danny Eytan

PLoS Comput. Biol., 2023

Robust Decision-Focused Learning for Reward Transfer.

Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez

CoRR, 2023

Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning.

Akhil Bagaria, Ben Abbatematteo, Omer Gottesman, Matt Corsaro, Sreehari Rammohan, George Dimitri Konidaris

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

TD Convergence: An Optimization Perspective.

Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs.

Haotian Fu, Jiayu Yao, Omer Gottesman, Finale Doshi-Velez, George Konidaris

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces.

Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael Littman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes.

Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez

CoRR, 2022

Faster Deep Reinforcement Learning with Slower Online Network.

Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation.

Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill

Proceedings of the Conference on Health, Inference, and Learning, 2022

Optimistic Initialization for Exploration in Continuous Control.

Sam Lobel, Omer Gottesman, Cameron Allen, Akhil Bagaria, George Konidaris

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Deep Q-Network with Proximal Iteration.

Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola

CoRR, 2021

Coarse-Grained Smoothness for RL in Metric Spaces.

Omer Gottesman, Kavosh Asadi, Cameron Allen, Sam Lobel, George Konidaris, Michael Littman

CoRR, 2021

Learning Markov State Abstractions for Deep Reinforcement Learning.

Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

State Relevance for Off-Policy Evaluation.

Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Learning to search efficiently for causally near-optimal treatments.

Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions.

Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

A general method for regularizing tensor decomposition methods via pseudo-data.

Omer Gottesman, Weiwei Pan, Finale Doshi-Velez

CoRR, 2019

Combining parametric and nonparametric models for off-policy evaluation.

Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters.

Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill

CoRR, 2018

Evaluating Reinforcement Learning Algorithms in Observational Health Settings.

Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-Wei H. Lehman, Andrew Slavin Ross, Aldo Faisal, Finale Doshi-Velez

Proceedings of the AMIA 2018, 2018

Weighted Tensor Decomposition for Learning Latent Variables with Partial Data.

Omer Gottesman, Weiwei Pan, Finale Doshi-Velez

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018