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Philip Amortila
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Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions
G Weisz, P Amortila, C Szepesvári
International Conference on Algorithmic Learning Theory (ALT) 2021, 2020
482020
Constrained Markov Decision Processes via Backward Value Functions
H Satija, P Amortila, J Pineau
International Conference on Machine Learning (ICML) 2020, 2020
282020
A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting
P Amortila, N Jiang, T Xie
arXiv preprint arXiv:2011.01075, 2020
122020
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function
G Weisz, P Amortila, B Janzer, Y Abbasi-Yadkori, N Jiang, C Szepesvári
Annual Conference on Learning Theory (COLT) 2021, 2021
112021
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms
P Amortila, D Precup, P Panangaden, MG Bellemare
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020
82020
Temporally Extended Metrics for Markov Decision Processes.
P Amortila, MG Bellemare, P Panangaden, D Precup
AAAI 2019 Safety in AI workshop, 2019
22019
Couplings in Reinforcement Learning: Applications to State Abstraction and Algorithm Analysis
P Amortila
McGill University, Masters Thesis, 2019
12019
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation
P Amortila, N Jiang, D Madeka, DP Foster
arXiv preprint arXiv:2207.08342, 2022
2022
Learning Graph Weighted Models on Pictures
P Amortila, G Rabusseau
International Conference on Grammatical Inference 2018, 2018
2018
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