Lazaric, Alessandro

102 publications

ICML 2025 Temporal Difference Flows Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Remi Munos, Alessandro Lazaric, Ahmed Touati

ICLRW 2025 Temporal Difference Flows Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Remi Munos, Alessandro Lazaric, Ahmed Touati

ICLR 2025 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta

ICLR 2024 Fast Imitation via Behavior Foundation Models Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

ICML 2024 Simple Ingredients for Offline Reinforcement Learning Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati

NeurIPSW 2024 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta

ICLR 2023 Contextual Bandits with Concave Rewards, and an Application to Fair Ranking Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier

NeurIPSW 2023 Fast Imitation via Behavior Foundation Models Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

TMLR 2023 Group Fairness in Reinforcement Learning Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau

ICML 2023 Layered State Discovery for Incremental Autonomous Exploration Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta

ICLR 2023 Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies Rui Yuan, Simon Shaolei Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao

AISTATS 2023 On the Complexity of Representation Learning in Contextual Linear Bandits Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

ALT 2023 Reaching Goals Is Hard: Settling the Sample Complexity of the Stochastic Shortest Path Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric

AISTATS 2022 A General Sample Complexity Analysis of Vanilla Policy Gradient Rui Yuan, Robert M. Gower, Alessandro Lazaric

AISTATS 2022 Adaptive Multi-Goal Exploration Jean Tarbouriech, Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Michal Valko, Alessandro Lazaric

AISTATS 2022 Top K Ranking for Multi-Armed Bandit with Noisy Evaluations Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta

ICLR 2022 A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du

ICLR 2022 Direct Then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching Pierre-Alexandre Kamienny, Jean Tarbouriech, Sylvain Lamprier, Alessandro Lazaric, Ludovic Denoyer

ICLRW 2022 Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto

CoRL 2022 Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Alessandro Lazaric, Karteek Alahari

ICLR 2022 Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

NeurIPS 2022 Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta

ICML 2022 Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco

UAI 2022 Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Denoyer Ludovic, Yoshua Bengio

NeurIPS 2021 A Provably Efficient Sample Collection Strategy for Reinforcement Learning Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric

ICMLW 2021 Direct Then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching Pierre-Alexandre Kamienny, Jean Tarbouriech, Alessandro Lazaric, Ludovic Denoyer

ICMLW 2021 Exploration-Driven Representation Learning in Reinforcement Learning Akram Erraqabi, Harry Zhao, Marlos C. Machado, Yoshua Bengio, Sainbayar Sukhbaatar, Ludovic Denoyer, Alessandro Lazaric

ICML 2021 Leveraging Good Representations in Linear Contextual Bandits Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

NeurIPSW 2021 Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

NeurIPS 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

ICML 2021 Reinforcement Learning with Prototypical Representations Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

ICLRW 2021 Reinforcement Learning with Prototypical Representations Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto

ALT 2021 Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric

NeurIPS 2021 Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret Jean Tarbouriech, Runlong Zhou, Simon S Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric

AISTATS 2020 A Novel Confidence-Based Algorithm for Structured Bandits Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

AISTATS 2020 A Single Algorithm for Both Restless and Rested Rotting Bandits Julien Seznec, Pierre Menard, Alessandro Lazaric, Michal Valko

UAI 2020 Active Model Estimation in Markov Decision Processes Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric

NeurIPS 2020 Adversarial Attacks on Linear Contextual Bandits Evrard Garcelon, Baptiste Roziere, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta

NeurIPS 2020 An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric

AISTATS 2020 Conservative Exploration in Reinforcement Learning Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta

ICML 2020 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation Marc Abeille, Alessandro Lazaric

AISTATS 2020 Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric

AAAI 2020 Improved Algorithms for Conservative Exploration in Bandits Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta

NeurIPS 2020 Improved Sample Complexity for Incremental Autonomous Exploration in MDPs Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric

ICML 2020 Learning near Optimal Policies with Low Inherent Bellman Error Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill

ICML 2020 Meta-Learning with Stochastic Linear Bandits Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil

ICML 2020 Near-Linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco

ICML 2020 No-Regret Exploration in Goal-Oriented Reinforcement Learning Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric

NeurIPS 2020 Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette, Alessandro Lazaric, Mykel J Kochenderfer, Emma Brunskill

NeurIPS 2019 A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning Nicolas Carion, Nicolas Usunier, Gabriel Synnaeve, Alessandro Lazaric

AISTATS 2019 Active Exploration in Markov Decision Processes Jean Tarbouriech, Alessandro Lazaric

NeurIPS 2019 Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric

COLT 2019 Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco

NeurIPS 2019 Limiting Extrapolation in Linear Approximate Value Iteration Andrea Zanette, Alessandro Lazaric, Mykel J Kochenderfer, Emma Brunskill

NeurIPS 2019 Regret Bounds for Learning State Representations in Reinforcement Learning Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, Odalric-Ambrym Maillard

AISTATS 2019 Rotting Bandits Are No Harder than Stochastic Ones Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko

ICML 2018 Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner

NeurIPS 2018 Fighting Boredom in Recommender Systems with Linear Reinforcement Learning Romain Warlop, Alessandro Lazaric, Jérémie Mary

ICML 2018 Improved Large-Scale Graph Learning Through Ridge Spectral Sparsification Daniele Calandriello, Alessandro Lazaric, Ioannis Koutis, Michal Valko

ICML 2018 Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems Marc Abeille, Alessandro Lazaric

NeurIPS 2018 Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes Ronan Fruit, Matteo Pirotta, Alessandro Lazaric

ICML 2017 Active Learning for Accurate Estimation of Linear Models Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric

AISTATS 2017 Distributed Adaptive Sampling for Kernel Matrix Approximation Daniele Calandriello, Alessandro Lazaric, Michal Valko

NeurIPS 2017 Efficient Second-Order Online Kernel Learning with Adaptive Embedding Daniele Calandriello, Alessandro Lazaric, Michal Valko

AISTATS 2017 Exploration-Exploitation in MDPs with Options Ronan Fruit, Alessandro Lazaric

AISTATS 2017 Linear Thompson Sampling Revisited Marc Abeille, Alessandro Lazaric

NeurIPS 2017 Regret Minimization in MDPs with Options Without Prior Knowledge Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Emma Brunskill

ICML 2017 Second-Order Kernel Online Convex Optimization with Adaptive Sketching Daniele Calandriello, Alessandro Lazaric, Michal Valko

AISTATS 2017 Thompson Sampling for Linear-Quadratic Control Problems Marc Abeille, Alessandro Lazaric

AISTATS 2017 Trading Off Rewards and Errors in Multi-Armed Bandits Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu

JMLR 2016 Analysis of Classification-Based Policy Iteration Algorithms Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos

UAI 2016 Analysis of Nyström Method with Sequential Ridge Leverage Scores Daniele Calandriello, Alessandro Lazaric, Michal Valko

AISTATS 2016 Improved Learning Complexity in Combinatorial Pure Exploration Bandits Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett

COLT 2016 Open Problem: Approximate Planning of POMDPs in the Class of Memoryless Policies Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

COLT 2016 Reinforcement Learning of POMDPs Using Spectral Methods Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar

IJCAI 2015 Direct Policy Iteration with Demonstrations Jessica Chemali, Alessandro Lazaric

IJCAI 2015 Maximum Entropy Semi-Supervised Inverse Reinforcement Learning Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh

NeurIPS 2014 Best-Arm Identification in Linear Bandits Marta Soare, Alessandro Lazaric, Remi Munos

NeurIPS 2014 Exploiting Easy Data in Online Optimization Amir Sani, Gergely Neu, Alessandro Lazaric

ICML 2014 Online Stochastic Optimization Under Correlated Bandit Feedback Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

NeurIPS 2014 Sparse Multi-Task Reinforcement Learning Daniele Calandriello, Alessandro Lazaric, Marcello Restelli

ECML-PKDD 2013 Regret Bounds for Reinforcement Learning with Policy Advice Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

NeurIPS 2013 Sequential Transfer in Multi-Armed Bandit with Finite Set of Models Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill

ICML 2012 A Dantzig Selector Approach to Temporal Difference Learning Matthieu Geist, Bruno Scherrer, Alessandro Lazaric, Mohammad Ghavamzadeh

NeurIPS 2012 Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric

AAAI 2012 Conservative and Greedy Approaches to Classification-Based Policy Iteration Mohammad Ghavamzadeh, Alessandro Lazaric

JMLR 2012 Finite-Sample Analysis of Least-Squares Policy Iteration Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos

NeurIPS 2012 Risk-Aversion in Multi-Armed Bandits Amir Sani, Alessandro Lazaric, Rémi Munos

ICML 2011 Classification-Based Policy Iteration with a Critic Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Bruno Scherrer

ICML 2011 Finite-Sample Analysis of Lasso-TD Mohammad Ghavamzadeh, Alessandro Lazaric, Rémi Munos, Matthew W. Hoffman

NeurIPS 2011 Multi-Bandit Best Arm Identification Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck

NeurIPS 2011 Transfer from Multiple MDPs Alessandro Lazaric, Marcello Restelli

ALT 2011 Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer

ICML 2010 Analysis of a Classification-Based Policy Iteration Algorithm Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos

ICML 2010 Bayesian Multi-Task Reinforcement Learning Alessandro Lazaric, Mohammad Ghavamzadeh

ACML 2010 Finite-Sample Analysis of Bellman Residual Minimization Odalric-Ambrym Maillard, Remi Munos, Alessandro Lazaric, Mohammad Ghavamzadeh

ICML 2010 Finite-Sample Analysis of LSTD Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos

NeurIPS 2010 LSTD with Random Projections Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric Maillard, Rémi Munos

COLT 2009 Hybrid Stochastic-Adversarial On-Line Learning Alessandro Lazaric, Rémi Munos

ICML 2009 Workshop Summary: On-Line Learning with Limited Feedback Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári

ICML 2008 Transfer of Samples in Batch Reinforcement Learning Alessandro Lazaric, Marcello Restelli, Andrea Bonarini

NeurIPS 2007 Reinforcement Learning in Continuous Action Spaces Through Sequential Monte Carlo Methods Alessandro Lazaric, Marcello Restelli, Andrea Bonarini