Philip Amortila

According to our database, Philip Amortila authored at least 12 papers between 2018 and 2024.

Collaborative distances:

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

2024

Scalable Online Exploration via Coverability.

Philip Amortila, Dylan J. Foster, Akshay Krishnamurthy

CoRR, 2024

Mitigating Covariate Shift in Misspecified Regression with Applications to Reinforcement Learning.

Philip Amortila, Tongyi Cao, Akshay Krishnamurthy

CoRR, 2024

Harnessing Density Ratios for Online Reinforcement Learning.

Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie

CoRR, 2024

2023

The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation.

Philip Amortila, Nan Jiang, Csaba Szepesvári

Proceedings of the International Conference on Machine Learning, 2023

2022

A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation.

Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster

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

2021

On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function.

Gellért Weisz, Philip Amortila, Barnabás Janzer, Yasin Abbasi-Yadkori, Nan Jiang, Csaba Szepesvári

Proceedings of the Conference on Learning Theory, 2021

Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions.

Gellért Weisz, Philip Amortila, Csaba Szepesvári

Proceedings of the Algorithmic Learning Theory, 2021

2020

A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting.

Philip Amortila, Nan Jiang, Tengyang Xie

CoRR, 2020

Constrained Markov Decision Processes via Backward Value Functions.

Harsh Satija, Philip Amortila, Joelle Pineau

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

A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms.

Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Temporally Extended Metrics for Markov Decision Processes.

Philip Amortila, Marc G. Bellemare, Prakash Panangaden, Doina Precup

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19), 2019

2018

Learning Graph Weighted Models on Pictures.

Philip Amortila, Guillaume Rabusseau

Proceedings of the 14th International Conference on Grammatical Inference, 2018