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Odalric-Ambrym Maillard

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42232

	Local Dvoretzky-Kiefer-Wolfowitz confidence bands Odalric-Ambrym Maillard Mathematical Methods of Statistics, 2022, ⟨10.3103/S1066530721010038⟩ Article dans une revue hal-03780573v1
	Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits Lilian Besson , Emilie Kaufmann , Odalric-Ambrym Maillard , Julien Seznec Journal of Machine Learning Research, 2022 Article dans une revue hal-02006471v3
	Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs Mohammad Sadegh Talebi , Odalric-Ambrym Maillard Journal of Machine Learning Research, inPress, pp.1-36 Article dans une revue hal-01737142v1
	Boundary Crossing Probabilities for General Exponential Families Odalric-Ambrym Maillard Mathematical Methods of Statistics, 2018, 27, pp.1-31. ⟨10.3103/S1066530718010015⟩ Article dans une revue hal-01737150v1
	Streaming kernel regression with provably adaptive mean, variance, and regularization Audrey Durand , Odalric-Ambrym Maillard , Joelle Pineau Journal of Machine Learning Research, 2018, 1, pp.1 - 48 Article dans une revue hal-01927007v1
	The Non-stationary Stochastic Multi-armed Bandit Problem Robin Allesiardo , Raphaël Féraud , Odalric-Ambrym Maillard International Journal of Data Science and Analytics, 2017, 3 (4), pp.267-283. ⟨10.1007/s41060-017-0050-5⟩ Article dans une revue hal-01575000v1

	From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic Bandits Dorian Baudry , Patrick Saux , Odalric-Ambrym Maillard NeurIPS 2021 - 35th International Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia Communication dans un congrès hal-03421252v2
	Indexed Minimum Empirical Divergence for Unimodal Bandits Hassan Saber , Pierre Ménard , Odalric-Ambrym Maillard NeurIPS 2021 - International Conference on Neural Information Processing Systems, Dec 2021, Virtual-only Conference, United States Communication dans un congrès hal-03446617v1
	Reinforcement Learning in Parametric MDPs with Exponential Families Sayak Ray Chowdhury , Aditya Gopalan , Odalric-Ambrym Maillard International Conference on Artificial Intelligence and Statistics, 2021, San diego, United States. pp.1855-1863 Communication dans un congrès hal-03472116v1
	Stochastic bandits with groups of similar arms Fabien Pesquerel , Hassan Saber , Odalric-Ambrym Maillard NeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia Communication dans un congrès hal-03427597v1
	Optimal Thompson Sampling strategies for support-aware CVaR bandits Dorian Baudry , Romain Gautron , Emilie Kaufmann , Odalric-Ambrym Maillard 38th International Conference on Machine Learning, Jul 2021, Virtual, United States Communication dans un congrès hal-03447244v1
	Sub-sampling for Efficient Non-Parametric Bandit Exploration Dorian Baudry , Emilie Kaufmann , Odalric-Ambrym Maillard NeurIPS 2020, Dec 2020, Vancouver, Canada Communication dans un congrès hal-02977552v1
	Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay Réda Alami , Odalric-Ambrym Maillard , Raphael Féraud International Conference on Machine Learning, Jul 2020, Wien, Austria Communication dans un congrès hal-03021712v1
	Tightening Exploration in Upper Confidence Reinforcement Learning Hippolyte Bourel , Odalric-Ambrym Maillard , Mohammad Sadegh Talebi International Conference on Machine Learning, Jul 2020, Vienna, Austria Communication dans un congrès hal-03000664v1
	Model-Based Reinforcement Learning Exploiting State-Action Equivalence Mahsa Asadi , Mohammad Sadegh Talebi , Hippolyte Bourel , Odalric-Ambrym Maillard ACML 2019, Proceedings of Machine Learning Research, Nov 2019, Nagoya, Japan. pp.204 - 219 Communication dans un congrès hal-02378887v1
	Learning Multiple Markov Chains via Adaptive Allocation Mohammad Sadegh Talebi , Odalric-Ambrym Maillard Advances in Neural Information Processing Systems 32 (NIPS 2019), Dec 2019, Vancouver, Canada Communication dans un congrès hal-02387345v1
	Regret Bounds for Learning State Representations in Reinforcement Learning Ronald Ortner , Matteo Pirotta , Ronan Fruit , Alessandro Lazaric , Odalric-Ambrym Maillard Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada Communication dans un congrès hal-02375715v1
	Budgeted Reinforcement Learning in Continuous State Space Nicolas Carrara , Edouard Leurent , Romain Laroche , Tanguy Urvoy , Odalric-Ambrym Maillard Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada Communication dans un congrès hal-02375727v1
	Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay bounds Odalric-Ambrym Maillard Algorithmic Learning Theory, 2019, Chicago, United States. pp.1 - 23 Communication dans un congrès hal-02351665v1
	Practical Open-Loop Optimistic Planning Edouard Leurent , Odalric-Ambrym Maillard European Conference on Machine Learning, Sep 2019, Würzburg, Germany Communication dans un congrès hal-02375697v1
	Boundary Crossing for General Exponential Families Odalric-Ambrym Maillard Algorithmic Learning Theory, Oct 2017, Kyoto, Japan. pp.1 - 34 Communication dans un congrès hal-01615427v1
	Spectral Learning from a Single Trajectory under Finite-State Policies Borja Balle , Odalric-Ambrym Maillard International conference on Machine Learning, Jul 2017, Sidney, France Communication dans un congrès hal-01590940v1
	Efficient tracking of a growing number of experts Jaouad Mourtada , Odalric-Ambrym Maillard Algorithmic Learning Theory, Oct 2017, Tokyo, Japan. pp.1 - 23 Communication dans un congrès hal-01615424v1

	Optimal Strategies for Graph-Structured Bandits Hassan Saber , Pierre Ménard , Odalric-Ambrym Maillard 2020 Pré-publication, Document de travail hal-02891139v2
	Forced-exploration free Strategies for Unimodal Bandits Hassan Saber , Pierre Ménard , Odalric-Ambrym Maillard 2020 Pré-publication, Document de travail hal-02883907v1