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Differentially Private Exploration in Reinforcement Learning with Linear Representation


Dec 02, 2021
Paul Luyo, Evrard Garcelon, Alessandro Lazaric, Matteo Pirotta


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Adaptive Multi-Goal Exploration


Nov 23, 2021
Jean Tarbouriech, Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Michal Valko, Alessandro Lazaric


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Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection


Oct 27, 2021
Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

* Accepted at NeurIPS 2021 

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Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching


Oct 27, 2021
Pierre-Alexandre Kamienny, Jean Tarbouriech, Alessandro Lazaric, Ludovic Denoyer


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A general sample complexity analysis of vanilla policy gradient


Jul 23, 2021
Rui Yuan, Robert M. Gower, Alessandro Lazaric

* ICML 2021 Workshop on "Reinforcement learning theory" 

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Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning


Jul 20, 2021
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto


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A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs


Jun 24, 2021
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric


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A Unified Framework for Conservative Exploration


Jun 22, 2021
Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon S. Du


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Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret


Apr 22, 2021
Jean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric


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Leveraging Good Representations in Linear Contextual Bandits


Apr 08, 2021
Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta


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Reinforcement Learning with Prototypical Representations


Feb 22, 2021
Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto


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Improved Sample Complexity for Incremental Autonomous Exploration in MDPs


Dec 29, 2020
Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric

* NeurIPS 2020 

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An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits


Oct 23, 2020
Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric

* To appear at NeurIPS 2020 

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Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration


Aug 18, 2020
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill


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Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation


Jul 13, 2020
Marc Abeille, Alessandro Lazaric


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A Provably Efficient Sample Collection Strategy for Reinforcement Learning


Jul 13, 2020
Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric


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Improved Analysis of UCRL2 with Empirical Bernstein Inequality


Jul 10, 2020
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric

* Document in support of the tutorial at ALT 2019 

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A Novel Confidence-Based Algorithm for Structured Bandits


May 23, 2020
Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

* AISTATS 2020 

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Meta-learning with Stochastic Linear Bandits


May 18, 2020
Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil


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Learning Adaptive Exploration Strategies in Dynamic Environments Through Informed Policy Regularization


May 06, 2020
Pierre-Alexandre Kamienny, Matteo Pirotta, Alessandro Lazaric, Thibault Lavril, Nicolas Usunier, Ludovic Denoyer

* 18 pages 

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Active Model Estimation in Markov Decision Processes


Mar 06, 2020
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric


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Learning Near Optimal Policies with Low Inherent Bellman Error


Mar 05, 2020
Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill

* Minor fix 

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Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification


Feb 26, 2020
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco


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Adversarial Attacks on Linear Contextual Bandits


Feb 11, 2020
Evrard Garcelon, Baptiste Roziere, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta


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Improved Algorithms for Conservative Exploration in Bandits


Feb 08, 2020
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta


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Conservative Exploration in Reinforcement Learning


Feb 08, 2020
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta


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Concentration Inequalities for Multinoulli Random Variables


Jan 30, 2020
Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric

* Tutorial at ALT'19 on Regret Minimization in Infinite-Horizon Finite Markov Decision Processes 

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No-Regret Exploration in Goal-Oriented Reinforcement Learning


Jan 30, 2020
Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric


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