Odalric-Ambrym Maillard

Publications

Article dans une revue (17)

Leveraging priors on distribution functions for multi-arm bandits Sumit Vashishtha,Odalric-Ambrym Maillard Reinforcement Learning Journal, In press, 6, pp.1600-1623. ⟨10.48550/arXiv.2503.04518⟩ Article dans une revue hal-05310340v1
The Confusing Instance Principle for Online Linear Quadratic Control Waris Radji,Odalric-Ambrym Maillard Reinforcement Learning Journal, 2025, 6, pp.811-828 Article dans une revue hal-05322160v1
Bandits with Stochastic Corruption: Lower Bounds on Regret and Robust Optimistic Algorithms Timothée Mathieu,Debabrota Basu,Odalric-Ambrym Maillard Transactions on Machine Learning Research Journal, 2024 Article dans une revue hal-04615733v2
AdaStop: adaptive statistical testing for sound comparisons of Deep RL agents Timothée Mathieu,Riccardo Della Vecchia,Alena Shilova,Matheus Medeiros Centa,Hector Kohleret al. Transactions on Machine Learning Research Journal, 2024 Article dans une revue hal-04132861v2
A channel selection game for multi-operator LoRaWAN deployments Kinda Khawam,Hassan Fawaz,Samer Lahoud,Odalric-Ambrym Maillard,Steven Martin Computer Networks, 2022, 216, pp.109185. ⟨10.1016/j.comnet.2022.109185⟩ Article dans une revue hal-03937953v1
Reinforcement Learning for crop management Romain Gautron,Odalric-Ambrym Maillard,Philippe Preux,Marc Corbeels,Régis Sabbadin Computers and Electronics in Agriculture, 2022, 200, pp.107182. ⟨10.1016/j.compag.2022.107182⟩ Article dans une revue hal-03834290v1
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
Collaborative Algorithms for Online Personalized Mean Estimation Mahsa Asadi,Aurélien Bellet,Odalric-Ambrym Maillard,Marc Tommasi Transactions on Machine Learning Research Journal, 2022 Article dans une revue hal-03905917v1
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
Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs Mohammad Sadegh Talebi,Odalric-Ambrym Maillard Journal of Machine Learning Research, 2018, pp.1-36 Article dans une revue hal-01737142v1
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
Concentration inequalities for sampling without replacement Rémi Bardenet,Odalric-Ambrym Maillard Bernoulli, 2015, 21 (3), pp.1361-1385. ⟨10.3150/14-BEJ605⟩ Article dans une revue hal-01216652v1
Sub-sampling for Multi-armed Bandits Akram Baransi,Odalric-Ambrym Maillard,Shie Mannor Proceedings of the European Conference on Machine Learning, 2014, pp.13 Article dans une revue hal-01025651v2
Latent Bandits Odalric-Ambrym Maillard,Shie Mannor JFPDA, 2014, pp.05 Article dans une revue hal-00990804v1
Kullback-Leibler Upper Confidence Bounds for Optimal Sequential Allocation Olivier Cappé,Aurélien Garivier,Odalric-Ambrym Maillard,Rémi Munos,Gilles Stoltz Annals of Statistics, 2013, 41 (3), pp.1516-1541. ⟨10.1214/13-AOS1119⟩ Article dans une revue hal-00738209v2

Communication dans un congrès (46)

Hierarchical Subspaces of Policies for Continual Offline Reinforcement Learning Anthony Kobanda,Rémy Portelas,Odalric-Ambrym Maillard,Ludovic Denoyer MCDC Workshop at ICLR 2025, Apr 2025, Singapore, Singapore Communication dans un congrès hal-05126349v1
A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks Anthony Kobanda,Odalric-Ambrym Maillard,Rémy Portelas IEEE Conference on Games, Aug 2025, Lisboa, Portugal Communication dans un congrès hal-05126447v1
Bandits with Multimodal Structure Hassan Saber,Odalric-Ambrym Maillard RLC 2024 - Reinforcement Learning Conference, Aug 2024, Amherst Massachusetts, United States. pp.39 Communication dans un congrès hal-04711994v1
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption Shubhada Agrawal,Timothée Mathieu,Debabrota Basu,Odalric-Ambrym Maillard International Conference on Algorithmic Learning Theory (ALT), Feb 2024, San Diego (CA), United States. pp.74-124 Communication dans un congrès hal-04260464v1
Power Mean Estimation in Stochastic Monte-Carlo Tree Search Tuan Quang Tuan Dam,Odalric-Ambrym Maillard,Emilie Kaufmann Uncertainty in Artificial Intelligence, Jul 2024, Barcelona, Spain Communication dans un congrès hal-04714124v1
Farm-gym: A modular reinforcement learning platform for stochastic agronomic games Odalric-Ambrym Maillard,Timothée Mathieu,Debabrota Basu AIAFS 2023 - Artificial Intelligence for Agriculture and Food Systems, Feb 2023, Wahington DC, United States Communication dans un congrès hal-03960683v1
Logarithmic regret in communicating MDPs: Leveraging known dynamics with bandits Hassan Saber,Fabien Pesquerel,Odalric-Ambrym Maillard,Mohammad Sadegh Talebi Asian Conference on Machine Learning, Nov 2023, Istanbul, Turkey Communication dans un congrès hal-04241513v1
Risk-aware linear bandits with convex loss Patrick Saux,Odalric-Ambrym Maillard International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2023, Valencia, Spain Communication dans un congrès hal-04044440v1
Learning crop management by reinforcement: gym-DSSAT Romain Gautron,Emilio J Padrón,Philippe Preux,Julien Bigot,Odalric-Ambrym Maillardet al. AIAFS 2023 - 2nd AAAI Workshop on AI for Agriculture and Food Systems, Feb 2023, Washignton DC, United States Communication dans un congrès hal-03976393v1
Bregman Deviations of Generic Exponential Families Sayak Ray Chowdhury,Patrick Saux,Odalric-Ambrym Maillard,Aditya Gopalan Conference On Learning Theory (COLT), Jul 2023, Bangalore, India Communication dans un congrès hal-04161043v1
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & Planning Reda Ouhamma,Debabrota Basu,Odalric-Ambrym Maillard Proceedings of the AAAI Conference on Artificial Intelligence, Feb 2023, Washignton DC, United States. pp.9336-9344, ⟨10.1609/aaai.v37i8.26119⟩ Communication dans un congrès hal-03790997v2
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits Dorian Baudry,Fabien Pesquerel,Rémy Degenne,Odalric-Ambrym Maillard NeurIPS 2023 - Thirty-seventh Conference on Neural Information Processing Systems, Dec 2023, New Orleans (Louisiana), United States Communication dans un congrès hal-04337742v1
Risk-aware linear bandits with convex loss Patrick Saux,Odalric-Ambrym Maillard European Workshop on Reinforcement Learning, Sep 2022, Milan, Italy Communication dans un congrès hal-03776680v1
IMED-RL: Regret optimal learning of ergodic Markov decision processes Fabien Pesquerel,Odalric-Ambrym Maillard NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New-Orleans, United States Communication dans un congrès hal-03825423v1
Routine Bandits: Minimizing Regret on Recurring Problems Hassan Saber,Léo Saci,Odalric-Ambrym Maillard,Audrey Durand ECML-PKDD 2021, Sep 2021, Bilbao, Spain Communication dans un congrès hal-03286539v1
Improved Exploration in Factored Average-Reward MDPs Sadegh Talebi,Anders Jonsson,Odalric-Ambrym Maillard 24th International Conference on Artificial Intelligence and Statistics, 2021, San diego (virtual), United States Communication dans un congrès hal-03780564v1
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
Learning Value Functions in Deep Policy Gradients using Residual Variance Yannis Flet-Berliac,Reda Ouhamma,Odalric-Ambrym Maillard,Philippe Preux ICLR 2021 - International Conference on Learning Representations, May 2021, Vienna / Virtual, Austria Communication dans un congrès hal-02964174v3
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
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
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
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
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
Monte-Carlo Graph Search: the Value of Merging Similar States Edouard Leurent,Odalric-Ambrym Maillard ACML 2020 - 12th Asian Conference on Machine Learning, Nov 2020, Bangkok / Virtual, Thailand. pp.577 - 602 Communication dans un congrès hal-03004124v2
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
Robust-Adaptive Interval Predictive Control for Linear Uncertain Systems Edouard Leurent,Denis Efimov,Odalric-Ambrym Maillard CDC 2020 - 59th IEEE Conference on Decision and Control, Dec 2020, Jeju Island / Virtual, South Korea Communication dans un congrès hal-02942414v1
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs Edouard Leurent,Denis Efimov,Odalric-Ambrym Maillard NeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtual, Canada Communication dans un congrès hal-03004060v1
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
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
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
Budgeted Reinforcement Learning in Continuous State Space Nicolas Carrara,Edouard Leurent,Romain Laroche,Tanguy Urvoy,Odalric-Ambrym Maillardet al. Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada Communication dans un congrès hal-02375727v1
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
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
Approximate Robust Control of Uncertain Dynamical Systems Edouard Leurent,Yann Blanco,Denis Efimov,Odalric-Ambrym Maillard Proc. MLITS Workshop at NeurIPS, Dec 2018, Montreal, Canada Communication dans un congrès hal-01931744v2
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
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
Pliable rejection sampling Akram Erraqabi,Michal Valko,Alexandra Carpentier,Odalric-Ambrym Maillard International Conference on Machine Learning, Jun 2016, New York City, United States Communication dans un congrès hal-01322168v1
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning Ronald Ortner,Odalric-Ambrym Maillard,Daniil Ryabko International Conference on Algorithmic Learning Theory (ALT), Oct 2014, Bled, Slovenia. pp.140-154 Communication dans un congrès hal-01057562v1
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning Odalric-Ambrym Maillard,Phuong Nguyen,Ronald Ortner,Daniil Ryabko ICML - 30th International Conference on Machine Learning, 2013, Atlanta, USA, United States. pp.543-551 Communication dans un congrès hal-00778586v1
Competing with an Infinite Set of Models in Reinforcement Learning Phuong Nguyen,Odalric-Ambrym Maillard,Daniil Ryabko,Ronald Ortner AISTATS, 2013, Arizona, United States. pp.463-471 Communication dans un congrès hal-00823230v1
Selecting the State-Representation in Reinforcement Learning Odalric-Ambrym Maillard,Rémi Munos,Daniil Ryabko Neural Information Processing Systems, Dec 2011, Granada, Spain Communication dans un congrès hal-00639483v1
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences Odalric-Ambrym Maillard,Rémi Munos,Gilles Stoltz 24th Annual Conference on Learning Theory : COLT'11, Jul 2011, Budapest, Hungary. pp.18 Communication dans un congrès inria-00574987v2
Finite-Sample Analysis of Bellman Residual Minimization Odalric-Ambrym Maillard,Rémi Munos,Alessandro Lazaric,Mohammad Ghavamzadeh Asian Conference on Machine Learning, 2010, Japan Communication dans un congrès hal-00830212v1
Compressed Least-Squares Regression Odalric-Ambrym Maillard,Rémi Munos NIPS 2009, Dec 2009, Vancouver, Canada Communication dans un congrès inria-00419210v2

Poster de conférence (3)

Évaluation de critères de sélection de noyaux pour la régression Ridge à noyau dans un contexte de petits jeux de données Frédérick Fabre Ferber,Dominique Gay,Jean-Christophe Soulié,Jean Diatta,Odalric-Ambrym Maillard 24ème conférence francophone sur l'Extraction et la Gestion des Connaissances EGC 2024, Jan 2024, Dijon, France. RNTI E-40 Poster de conférence hal-04516719v1
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 Réunion Frédérick Fabre Ferber,Jean Diatta,Jean-Christophe Soulié,Dominique Gay,Odalric-Ambrym Maillardet al. Comité scientifique et technique du DPP CapTerre, Nov 2022, Saint-Gilles, La Réunion Poster de conférence hal-03971262v1
Memory Bandits: Towards the Switching Bandit Problem Best Resolution Réda Alami,Odalric-Ambrym Maillard,Raphaël Féraud MLSS 2018 - Machine Learning Summer School, Aug 2018, Madrid, Spain Poster de conférence hal-01879251v1

Autre publication scientifique (2)

Latent Bandits. Odalric-Ambrym Maillard,Shie Mannor 2014 Autre publication scientifique hal-00926281v1
Robust Risk-averse Stochastic Multi-Armed Bandits Odalric-Ambrym Maillard 2013 Autre publication scientifique hal-00821670v1

Pré-publication, Document de travail (16)

Adaptive Quasimetric Mapping : Principled Topological Abstraction for Robust Offline Goal-Conditioned Navigation Anthony Kobanda,Waris Radji,Odalric-Ambrym Maillard,Rémy Portelas 2026 Pré-publication, Document de travail hal-05495482v3
The Regret Lower Bound for communicating Markov Decision Processes Victor Boone,Odalric-Ambrym Maillard 2025 Pré-publication, Document de travail hal-05421579v1
Kriging and Gaussian Process Interpolation for Georeferenced Data Augmentation Frédérick Fabre Ferber,Dominique Gay,Jean-Christophe Soulié,Jean Diatta,Odalric-Ambrym Maillard 2025 Pré-publication, Document de travail hal-04879232v1
Asymptotically Optimal Problem-Dependent Bandit Policies for Transfer Learning Adrien Prevost,Timothee Mathieu,Odalric-Ambrym Maillard 2025 Pré-publication, Document de travail hal-05574210v1
How Hard is it to Confuse a World Model? Waris Radji,Odalric-Ambrym Maillard 2025 Pré-publication, Document de travail hal-05326972v1
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm Debabrota Basu,Odalric-Ambrym Maillard,Timothée Mathieu 2022 Pré-publication, Document de travail hal-03611816v1
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
Active Roll-outs in MDP with Irreversible Dynamics Odalric-Ambrym Maillard,Timothy Mann,Ronald Ortner,Shie Mannor 2019 Pré-publication, Document de travail hal-02177808v1
Upper Confidence Reinforcement Learning exploiting state-action equivalence Odalric-Ambrym Maillard,Mahsa Asadi 2018 Pré-publication, Document de travail hal-01945034v1
Random Shuffling and Resets for the Non-stationary Stochastic Bandit Problem Robin Allesiardo,Raphaël Féraud,Odalric-Ambrym Maillard 2016 Pré-publication, Document de travail hal-01400320v1
Low-rank Bandits with Latent Mixtures Aditya Gopalan,Odalric-Ambrym Maillard,Mohammadi Zaki 2016 Pré-publication, Document de travail hal-01400318v1
Self-normalization techniques for streaming confident regression Odalric-Ambrym Maillard 2016 Pré-publication, Document de travail hal-01349727v2
A note on replacing uniform subsampling by random projections in MCMC for linear regression of tall datasets Rémi Bardenet,Odalric-Ambrym Maillard 2015 Pré-publication, Document de travail hal-01248841v1
Hierarchical Optimistic Region Selection driven by Curiosity Odalric-Ambrym Maillard 2012 Pré-publication, Document de travail hal-00740418v1
Online allocation and homogeneous partitioning for piecewise constant mean-approximation Odalric-Ambrym Maillard,Alexandra Carpentier 2012 Pré-publication, Document de travail hal-00742893v1

Rapport (4)

gym-DSSAT: a crop model turned into a Reinforcement Learning environment Romain Gautron,Emilio J. Padrón,Philippe Preux,Julien Bigot,Odalric-Ambrym Maillardet al. [Research Report] RR-9460, Inria Lille. 2022, pp.31 Rapport hal-03711132v4
Adaptive Bandits: Towards the best history-dependent strategy Odalric-Ambrym Maillard,Rémi Munos [Technical Report] 2011, pp.14 Rapport (rapport technique) inria-00574999v1
Brownian Motions and Scrambled Wavelets for Least-Squares Regression Odalric-Ambrym Maillard,Rémi Munos [Technical Report] 2010, pp.13 Rapport (rapport technique) inria-00483017v1
Linear regression with random projections Odalric-Ambrym Maillard,Rémi Munos [Technical Report] 2010, pp.22 Rapport (rapport technique) inria-00483014v2

Thèse (1)

APPRENTISSAGE SÉQUENTIEL : Bandits, Statistique et Renforcement. Odalric-Ambrym Maillard Machine Learning [cs.LG]. Université des Sciences et Technologie de Lille - Lille I, 2011. English. ⟨NNT : ⟩ Thèse tel-00845410v1

HDR (1)

Mathematics of Statistical Sequential Decision Making Odalric-Ambrym Maillard Mathematics [math]. Université de Lille, Sciences et Technologies, 2019 HDR tel-02162189v3

Cours (1)

Basic Concentration Properties of Real-Valued Distributions Odalric-Ambrym Maillard Doctoral. France. 2017 Cours cel-01632228v1