Stebėti
Scott Fujimoto
Scott Fujimoto
Patvirtintas el. paštas mail.mcgill.ca
Pavadinimas
Cituota
Cituota
Metai
Addressing Function Approximation Error in Actor-Critic Methods
S Fujimoto, H van Hoof, D Meger
Proceedings of the 35th International Conference on Machine Learning 80 …, 2018
50172018
Off-Policy Deep Reinforcement Learning without Exploration
S Fujimoto, D Meger, D Precup
Proceedings of the 36th International Conference on Machine Learning 97 …, 2019
13812019
A minimalist approach to offline reinforcement learning
S Fujimoto, SS Gu
Advances in neural information processing systems 34, 20132-20145, 2021
5432021
Benchmarking Batch Deep Reinforcement Learning Algorithms
S Fujimoto, E Conti, M Ghavamzadeh, J Pineau
Deep Reinforcement Learning Workshop NeurIPS 2019, 2019
1892019
Horizon: Facebook's Open Source Applied Reinforcement Learning Platform
J Gauci, E Conti, Y Liang, K Virochsiri, Y He, Z Kaden, V Narayanan, X Ye, ...
Reinforcement Learning for Real Life Workshop in the 36th International …, 2019
1552019
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
EJ Smith, S Fujimoto, A Romero, D Meger
Proceedings of the 36th International Conference on Machine Learning 97 …, 2019
1052019
Sentiment analysis: It’s complicated!
K Kenyon-Dean, E Ahmed, S Fujimoto, J Georges-Filteau, C Glasz, ...
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
872018
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
S Fujimoto, D Meger, D Precup
Advances in Neural Information Processing Systems 33, 14219-14230, 2020
562020
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation
E Smith, S Fujimoto, D Meger
Advances in Neural Information Processing Systems 31, 6477-6487, 2018
512018
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error
S Fujimoto, D Meger, D Precup, O Nachum, SS Gu
Proceedings of the 39th International Conference on Machine Learning 162 …, 2022
242022
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
S Fujimoto, D Meger, D Precup
Proceedings of the 38th International Conference on Machine Learning 139 …, 2021
162021
For SALE: State-Action Representation Learning for Deep Reinforcement Learning
S Fujimoto, WD Chang, E Smith, SS Gu, D Precup, D Meger
Advances in Neural Information Processing Systems 36, 2023
122023
IL-flOw: Imitation Learning from Observation using Normalizing Flows
WD Chang, JCG Higuera, S Fujimoto, D Meger, G Dudek
Robot Learning Workshop NeurIPS 2021, 2021
102021
Imitation Learning from Observation through Optimal Transport
WD Chang, S Fujimoto, D Meger, G Dudek
arXiv preprint arXiv:2310.01632, 2023
12023
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