Omar Darwiche Domingues

According to our database, Omar Darwiche Domingues authored at least 11 papers between 2019 and 2022.

Collaborative distances:

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

2022

Exploration in Reinforcement Learning: Beyond Finite State-Spaces. (Exploration en apprentissage par renforcement : au-delà des espaces d'états finis).

Omar Darwiche Domingues

PhD thesis, 2022

Adaptive Multi-Goal Exploration.

Jean Tarbouriech, Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Michal Valko, Alessandro Lazaric

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

UCB Momentum Q-learning: Correcting the bias without forgetting.

Pierre Ménard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko

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

Fast active learning for pure exploration in reinforcement learning.

Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko

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

Kernel-Based Reinforcement Learning: A Finite-Time Analysis.

Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko

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

Adaptive Reward-Free Exploration.

Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko

Proceedings of the Algorithmic Learning Theory, 2021

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited.

Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko

Proceedings of the Algorithmic Learning Theory, 2021

A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces.

Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Regret Bounds for Kernel-Based Reinforcement Learning.

Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko

CoRR, 2020

Planning in Markov Decision Processes with Gap-Dependent Sample Complexity.

Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko

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

2019

Planning in entropy-regularized Markov decision processes and games.

Jean-Bastien Grill, Omar Darwiche Domingues, Pierre Ménard, Rémi Munos, Michal Valko

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019