Thomas, Philip

15 publications

AISTATS 2023 Asymptotically Unbiased Off-Policy Policy Evaluation When Reusing Old Data in Nonstationary Environments Vincent Liu, Yash Chandak, Philip Thomas, Martha White

ICML 2021 High Confidence Generalization for Reinforcement Learning James Kostas, Yash Chandak, Scott M Jordan, Georgios Theocharous, Philip Thomas

ICML 2021 Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods Chris Nota, Philip Thomas, Bruno C. Da Silva

ICML 2021 Towards Practical Mean Bounds for Small Samples My Phan, Philip Thomas, Erik Learned-Miller

ICML 2020 Asynchronous Coagent Networks James Kostas, Chris Nota, Philip Thomas

ICML 2020 Evaluating the Performance of Reinforcement Learning Algorithms Scott Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas

ICML 2020 Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas

ICML 2019 Concentration Inequalities for Conditional Value at Risk Philip Thomas, Erik Learned-Miller

ICML 2019 Learning Action Representations for Reinforcement Learning Yash Chandak, Georgios Theocharous, James Kostas, Scott Jordan, Philip Thomas

ICML 2018 Decoupling Gradient-like Learning Rules from Representations Philip Thomas, Christoph Dann, Emma Brunskill

ICML 2016 Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning Philip Thomas, Emma Brunskill

ICML 2016 Energetic Natural Gradient Descent Philip Thomas, Bruno Castro Silva, Christoph Dann, Emma Brunskill

ICML 2015 High Confidence Policy Improvement Philip Thomas, Georgios Theocharous, Mohammad Ghavamzadeh

ICML 2014 Bias in Natural Actor-Critic Algorithms Philip Thomas

ICML 2014 GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results Philip Thomas