Odalric-Ambrym Maillard
83
Documents
Publications
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Power Mean Estimation in Stochastic Monte-Carlo Tree SearchUncertainty in Artificial Intelligence, Jul 2024, Barcelona, Spain
Conference papers
hal-04714124v1
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Bandits with Multimodal StructureRLC 2024 - Reinforcement Learning Conference, Aug 2024, Amherst Massachusetts, United States. pp.39
Conference papers
hal-04711994v1
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CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic CorruptionInternational Conference on Algorithmic Learning Theory (ALT), Feb 2024, San Diego (CA), United States. pp.74-124
Conference papers
hal-04260464v1
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Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic BanditsNeurIPS 2023 - Thirty-seventh Conference on Neural Information Processing Systems, Dec 2023, New Orleans (Louisiana), United States
Conference papers
hal-04337742v1
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Bregman Deviations of Generic Exponential FamiliesConference On Learning Theory (COLT), Jul 2023, Bangalore, India
Conference papers
hal-04161043v1
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Learning crop management by reinforcement: gym-DSSATAIAFS 2023 - 2nd AAAI Workshop on AI for Agriculture and Food Systems, Feb 2023, Washignton DC, United States
Conference papers
hal-03976393v1
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Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & PlanningProceedings of the AAAI Conference on Artificial Intelligence, Feb 2023, Washignton DC, United States. pp.9336-9344, ⟨10.1609/aaai.v37i8.26119⟩
Conference papers
hal-03790997v2
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Farm-gym: A modular reinforcement learning platform for stochastic agronomic gamesAIAFS 2023 - Artificial Intelligence for Agriculture and Food Systems, Feb 2023, Wahington DC, United States
Conference papers
hal-03960683v1
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Logarithmic regret in communicating MDPs: Leveraging known dynamics with banditsAsian Conference on Machine Learning, Nov 2023, Istanbul, Turkey
Conference papers
hal-04241513v1
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Risk-aware linear bandits with convex lossInternational Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2023, Valencia, Spain
Conference papers
hal-04044440v1
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IMED-RL: Regret optimal learning of ergodic Markov decision processesNeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New-Orleans, United States
Conference papers
hal-03825423v1
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Risk-aware linear bandits with convex lossEuropean Workshop on Reinforcement Learning, Sep 2022, Milan, Italy
Conference papers
hal-03776680v1
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Stochastic bandits with groups of similar armsNeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia
Conference papers
hal-03427597v1
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Improved Exploration in Factored Average-Reward MDPs24th International Conference on Artificial Intelligence and Statistics, 2021, San diego (virtual), United States
Conference papers
hal-03780564v1
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Learning Value Functions in Deep Policy Gradients using Residual VarianceICLR 2021 - International Conference on Learning Representations, May 2021, Vienna / Virtual, Austria
Conference papers
hal-02964174v3
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From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic BanditsNeurIPS 2021 - 35th International Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia
Conference papers
hal-03421252v2
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Indexed Minimum Empirical Divergence for Unimodal BanditsNeurIPS 2021 - International Conference on Neural Information Processing Systems, Dec 2021, Virtual-only Conference, United States
Conference papers
hal-03446617v1
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Routine Bandits: Minimizing Regret on Recurring ProblemsECML-PKDD 2021, Sep 2021, Bilbao, Spain
Conference papers
hal-03286539v1
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Reinforcement Learning in Parametric MDPs with Exponential FamiliesInternational Conference on Artificial Intelligence and Statistics, 2021, San diego, United States. pp.1855-1863
Conference papers
hal-03472116v1
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Optimal Thompson Sampling strategies for support-aware CVaR bandits38th International Conference on Machine Learning, Jul 2021, Virtual, United States
Conference papers
hal-03447244v1
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Tightening Exploration in Upper Confidence Reinforcement LearningInternational Conference on Machine Learning, Jul 2020, Vienna, Austria
Conference papers
hal-03000664v1
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Monte-Carlo Graph Search: the Value of Merging Similar StatesACML 2020 - 12th Asian Conference on Machine Learning, Nov 2020, Bangkok / Virtual, Thailand. pp.577 - 602
Conference papers
hal-03004124v2
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Sub-sampling for Efficient Non-Parametric Bandit ExplorationNeurIPS 2020, Dec 2020, Vancouver, Canada
Conference papers
hal-02977552v1
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Robust-Adaptive Interval Predictive Control for Linear Uncertain SystemsCDC 2020 - 59th IEEE Conference on Decision and Control, Dec 2020, Jeju Island / Virtual, South Korea
Conference papers
hal-02942414v1
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Robust-Adaptive Control of Linear Systems: beyond Quadratic CostsNeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtual, Canada
Conference papers
hal-03004060v1
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Restarted Bayesian Online Change-point Detector achieves Optimal Detection DelayInternational Conference on Machine Learning, Jul 2020, Wien, Austria
Conference papers
hal-03021712v1
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Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay boundsAlgorithmic Learning Theory, 2019, Chicago, United States. pp.1 - 23
Conference papers
hal-02351665v1
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Budgeted Reinforcement Learning in Continuous State SpaceConference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada
Conference papers
hal-02375727v1
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Model-Based Reinforcement Learning Exploiting State-Action EquivalenceACML 2019, Proceedings of Machine Learning Research, Nov 2019, Nagoya, Japan. pp.204 - 219
Conference papers
hal-02378887v1
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Practical Open-Loop Optimistic PlanningEuropean Conference on Machine Learning, Sep 2019, Würzburg, Germany
Conference papers
hal-02375697v1
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Regret Bounds for Learning State Representations in Reinforcement LearningConference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada
Conference papers
hal-02375715v1
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Learning Multiple Markov Chains via Adaptive AllocationAdvances in Neural Information Processing Systems 32 (NIPS 2019), Dec 2019, Vancouver, Canada
Conference papers
hal-02387345v1
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Approximate Robust Control of Uncertain Dynamical SystemsProc. MLITS Workshop at NeurIPS, Dec 2018, Montreal, Canada
Conference papers
hal-01931744v2
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Efficient tracking of a growing number of expertsAlgorithmic Learning Theory, Oct 2017, Tokyo, Japan. pp.1 - 23
Conference papers
hal-01615424v1
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Boundary Crossing for General Exponential FamiliesAlgorithmic Learning Theory, Oct 2017, Kyoto, Japan. pp.1 - 34
Conference papers
hal-01615427v1
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Spectral Learning from a Single Trajectory under Finite-State PoliciesInternational conference on Machine Learning, Jul 2017, Sidney, France
Conference papers
hal-01590940v1
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Pliable rejection samplingInternational Conference on Machine Learning, Jun 2016, New York City, United States
Conference papers
hal-01322168v1
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Selecting Near-Optimal Approximate State Representations in Reinforcement LearningInternational Conference on Algorithmic Learning Theory (ALT), Oct 2014, Bled, Slovenia. pp.140-154
Conference papers
hal-01057562v1
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Optimal Regret Bounds for Selecting the State Representation in Reinforcement LearningICML - 30th International Conference on Machine Learning, 2013, Atlanta, USA, United States. pp.543-551
Conference papers
hal-00778586v1
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Competing with an Infinite Set of Models in Reinforcement LearningAISTATS, 2013, Arizona, United States. pp.463-471
Conference papers
hal-00823230v1
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A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences24th Annual Conference on Learning Theory : COLT'11, Jul 2011, Budapest, Hungary. pp.18
Conference papers
inria-00574987v2
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Selecting the State-Representation in Reinforcement LearningNeural Information Processing Systems, Dec 2011, Granada, Spain
Conference papers
hal-00639483v1
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Finite-Sample Analysis of Bellman Residual MinimizationAsian Conference on Machine Learning, 2010, Japan
Conference papers
hal-00830212v1
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Compressed Least-Squares RegressionNIPS 2009, Dec 2009, Vancouver, Canada
Conference papers
inria-00419210v2
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Évaluation de critères de sélection de noyaux pour la régression Ridge à noyau dans un contexte de petits jeux de données24ème conférence francophone sur l'Extraction et la Gestion des Connaissances EGC 2024, Jan 2024, Dijon, France. RNTI E-40
Conference poster
hal-04516719v1
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Petits jeux de données et prédiction en Intelligence Artificielle, vers une meilleure cohabitation : Application à la gestion durable de l'enherbement des systèmes agricoles à La RéunionComité scientifique et technique du DPP CapTerre, Nov 2022, Saint-Leu de La Réunion, Réunion
Conference poster
hal-03971262v1
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Memory Bandits: Towards the Switching Bandit Problem Best ResolutionMLSS 2018 - Machine Learning Summer School, Aug 2018, Madrid, Spain
Conference poster
hal-01879251v1
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Latent Bandits.2014
Other publications
hal-00926281v1
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Robust Risk-averse Stochastic Multi-Armed Bandits2013
Other publications
hal-00821670v1
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gym-DSSAT: a crop model turned into a Reinforcement Learning environment[Research Report] RR-9460, Inria Lille. 2022, pp.31
Reports
hal-03711132v4
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Adaptive Bandits: Towards the best history-dependent strategy[Technical Report] 2011, pp.14
Reports
inria-00574999v1
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Brownian Motions and Scrambled Wavelets for Least-Squares Regression[Technical Report] 2010, pp.13
Reports
inria-00483017v1
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Linear regression with random projections[Technical Report] 2010, pp.22
Reports
inria-00483014v2
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APPRENTISSAGE SÉQUENTIEL : Bandits, Statistique et Renforcement.Machine Learning [cs.LG]. Université des Sciences et Technologie de Lille - Lille I, 2011. English. ⟨NNT : ⟩
Theses
tel-00845410v1
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Mathematics of Statistical Sequential Decision MakingMathematics [math]. Université de Lille, Sciences et Technologies, 2019
Accreditation to supervise research
tel-02162189v3
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Basic Concentration Properties of Real-Valued DistributionsDoctoral. France. 2017
Lectures
cel-01632228v1
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