Alessandro Lazaric

199 papers A* 55A 22B 4C 1Misc 1Journal 87Unranked 27

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Compositional Planning with Jumpy World Models. CoRR Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Marc G. Bellemare, Alessandro Lazaric, Ahmed Touati
2025	J	`jnl`	BFM-Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning. CoRR Yitang Li, Zhengyi Luo, Tonghe Zhang, Cunxi Dai, Anssi Kanervisto, Andrea Tirinzoni, Haoyang Weng, Kris Kitani, Mateusz Guzek, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta, Guanya Shi
2025	J	`jnl`	Embodied AI Agents: Modeling the World. CoRR Pascale Fung, Yoram Bachrach, Asli Celikyilmaz, Kamalika Chaudhuri, Delong Chen, Willy Chung, Emmanuel Dupoux, Hervé Jégou, Alessandro Lazaric, Arjun Majumdar, Andrea Madotto, Franziska Meier, Florian Metze, Théo Moutakanni, Juan Pino, Basile Terver, Joseph Tighe, Jitendra Malik
2025	J	`jnl`	Fast Adaptation with Behavioral Foundation Models. CoRR Harshit Sikchi, Andrea Tirinzoni, Ahmed Touati, Yingchen Xu, Anssi Kanervisto, Scott Niekum, Amy Zhang, Alessandro Lazaric, Matteo Pirotta
2025	J	`jnl`	TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning. CoRR Marco Bagatella, Matteo Pirotta, Ahmed Touati, Alessandro Lazaric, Andrea Tirinzoni
2025	A*	`conf`	Temporal Difference Flows. ICML Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Rémi Munos, Alessandro Lazaric, Ahmed Touati
2025	J	`jnl`	Temporal Difference Flows. CoRR Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Rémi Munos, Alessandro Lazaric, Ahmed Touati
2025	A*	`conf`	Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models. ICLR Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
2025	J	`jnl`	Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models. CoRR Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
2024	A*	`conf`	Fast Imitation via Behavior Foundation Models. ICLR Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier
2024	J	`jnl`	Reinforcement Learning with Options and State Representation. CoRR Ayoub Ghriss, Masashi Sugiyama, Alessandro Lazaric
2024	A*	`conf`	Simple Ingredients for Offline Reinforcement Learning. ICML Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
2024	J	`jnl`	Simple Ingredients for Offline Reinforcement Learning. CoRR Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
2024	—	`conf`	System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. FAccT Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel
2024	J	`jnl`	System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. CoRR Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel
2023	A*	`conf`	Contextual bandits with concave rewards, and an application to fair ranking. ICLR Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier
2023	J	`jnl`	Group Fairness in Reinforcement Learning. Trans. Mach. Learn. Res. Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau
2023	A*	`conf`	Layered State Discovery for Incremental Autonomous Exploration. ICML Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta
2023	J	`jnl`	Layered State Discovery for Incremental Autonomous Exploration. CoRR Liyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta
2023	J	`jnl`	Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping. CoRR Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Alessandro Lazaric, Karteek Alahari
2023	A*	`conf`	Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies. ICLR Rui Yuan, Simon Shaolei Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao
2023	A	`conf`	On the Complexity of Representation Learning in Contextual Linear Bandits. AISTATS Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
2023	B	`conf`	Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. ALT Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
2022	A*	`conf`	A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. ICLR Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du
2022	A	`conf`	A general sample complexity analysis of vanilla policy gradient. AISTATS Rui Yuan, Robert M. Gower, Alessandro Lazaric
2022	A	`conf`	Adaptive Multi-Goal Exploration. AISTATS Jean Tarbouriech, Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2022	J	`jnl`	Contextual bandits with concave rewards, and an application to fair ranking. CoRR Virginie Do, Elvis Dohmatob, Matteo Pirotta, Alessandro Lazaric, Nicolas Usunier
2022	A*	`conf`	Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching. ICLR Pierre-Alexandre Kamienny, Jean Tarbouriech, Sylvain Lamprier, Alessandro Lazaric, Ludovic Denoyer
2022	J	`jnl`	Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
2022	J	`jnl`	Improved Adaptive Algorithm for Scalable Active Learning with Weak Labeler. CoRR Yifang Chen, Karthik Abinav Sankararaman, Alessandro Lazaric, Matteo Pirotta, Dmytro Karamshuk, Qifan Wang, Karishma Mandyam, Sinong Wang, Han Fang
2022	Misc	`conf`	Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping. CoRL Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski, Alessandro Lazaric, Karteek Alahari
2022	J	`jnl`	Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies. CoRR Rui Yuan, Simon S. Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao
2022	A*	`conf`	Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. ICLR Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
2022	J	`jnl`	On the Complexity of Representation Learning in Contextual Linear Bandits. CoRR Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
2022	J	`jnl`	Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. CoRR Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
2022	A*	`conf`	Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. NeurIPS Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
2022	J	`jnl`	Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. CoRR Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta
2022	A*	`conf`	Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times. ICML Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2022	J	`jnl`	Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times. CoRR Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2022	J	`jnl`	Sketched Newton-Raphson. SIAM J. Optim. Rui Yuan, Alessandro Lazaric, Robert M. Gower
2022	J	`jnl`	Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL. CoRR Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio
2022	A	`conf`	Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. UAI Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio
2022	A	`conf`	Top K Ranking for Multi-Armed Bandit with Noisy Evaluations. AISTATS Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs. CoRR Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
2021	A*	`conf`	A Provably Efficient Sample Collection Strategy for Reinforcement Learning. NeurIPS Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2021	J	`jnl`	A Unified Framework for Conservative Exploration. CoRR Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon S. Du
2021	J	`jnl`	A general sample complexity analysis of vanilla policy gradient. CoRR Rui Yuan, Robert M. Gower, Alessandro Lazaric
2021	J	`jnl`	Adaptive Multi-Goal Exploration. CoRR Jean Tarbouriech, Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2021	J	`jnl`	Differentially Private Exploration in Reinforcement Learning with Linear Representation. CoRR Paul Luyo, Evrard Garcelon, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching. CoRR Pierre-Alexandre Kamienny, Jean Tarbouriech, Sylvain Lamprier, Alessandro Lazaric, Ludovic Denoyer
2021	A*	`conf`	Leveraging Good Representations in Linear Contextual Bandits. ICML Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Leveraging Good Representations in Linear Contextual Bandits. CoRR Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. CoRR Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
2021	A*	`conf`	Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. NeurIPS Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	J	`jnl`	Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. CoRR Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
2021	A*	`conf`	Reinforcement Learning with Prototypical Representations. ICML Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
2021	J	`jnl`	Reinforcement Learning with Prototypical Representations. CoRR Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto
2021	B	`conf`	Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model. ALT Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2021	A*	`conf`	Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret. NeurIPS Jean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2021	J	`jnl`	Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret. CoRR Jean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2021	J	`jnl`	Top K Ranking for Multi-Armed Bandit with Noisy Evaluations. CoRR Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta
2020	A	`conf`	A Novel Confidence-Based Algorithm for Structured Bandits. AISTATS Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli
2020	J	`jnl`	A Novel Confidence-Based Algorithm for Structured Bandits. CoRR Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli
2020	J	`jnl`	A Provably Efficient Sample Collection Strategy for Reinforcement Learning. CoRR Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2020	A	`conf`	A single algorithm for both restless and rested rotting bandits. AISTATS Julien Seznec, Pierre Ménard, Alessandro Lazaric, Michal Valko
2020	A	`conf`	Active Model Estimation in Markov Decision Processes. UAI Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
2020	J	`jnl`	Active Model Estimation in Markov Decision Processes. CoRR Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta, Mohammad Ghavamzadeh, Alessandro Lazaric
2020	A*	`conf`	Adversarial Attacks on Linear Contextual Bandits. NeurIPS Evrard Garcelon, Baptiste Rozière, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Adversarial Attacks on Linear Contextual Bandits. CoRR Evrard Garcelon, Baptiste Rozière, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta
2020	A*	`conf`	An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits. NeurIPS Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric
2020	J	`jnl`	An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits. CoRR Andrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric
2020	J	`jnl`	Concentration Inequalities for Multinoulli Random Variables. CoRR Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2020	A	`conf`	Conservative Exploration in Reinforcement Learning. AISTATS Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Conservative Exploration in Reinforcement Learning. CoRR Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	A*	`conf`	Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation. ICML Marc Abeille, Alessandro Lazaric
2020	J	`jnl`	Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation. CoRR Marc Abeille, Alessandro Lazaric
2020	A	`conf`	Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. AISTATS Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric
2020	A*	`conf`	Improved Algorithms for Conservative Exploration in Bandits. AAAI Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Improved Algorithms for Conservative Exploration in Bandits. CoRR Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta
2020	J	`jnl`	Improved Analysis of UCRL2 with Empirical Bernstein Inequality. CoRR Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2020	A*	`conf`	Improved Sample Complexity for Incremental Autonomous Exploration in MDPs. NeurIPS Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2020	J	`jnl`	Improved Sample Complexity for Incremental Autonomous Exploration in MDPs. CoRR Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric
2020	J	`jnl`	Learning Adaptive Exploration Strategies in Dynamic Environments Through Informed Policy Regularization. CoRR Pierre-Alexandre Kamienny, Matteo Pirotta, Alessandro Lazaric, Thibault Lavril, Nicolas Usunier, Ludovic Denoyer
2020	A*	`conf`	Learning Near Optimal Policies with Low Inherent Bellman Error. ICML Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	J	`jnl`	Learning Near Optimal Policies with Low Inherent Bellman Error. CoRR Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	A*	`conf`	Meta-learning with Stochastic Linear Bandits. ICML Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
2020	J	`jnl`	Meta-learning with Stochastic Linear Bandits. CoRR Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
2020	J	`jnl`	Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification. CoRR Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2020	A*	`conf`	Near-linear time Gaussian process optimization with adaptive batching and resparsification. ICML Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2020	A*	`conf`	No-Regret Exploration in Goal-Oriented Reinforcement Learning. ICML Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric
2020	A*	`conf`	Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. NeurIPS Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	J	`jnl`	Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. CoRR Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	J	`jnl`	Sketched Newton-Raphson. CoRR Rui Yuan, Alessandro Lazaric, Robert M. Gower
2019	A*	`conf`	A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning. NeurIPS Nicolas Carion, Nicolas Usunier, Gabriel Synnaeve, Alessandro Lazaric
2019	J	`jnl`	A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning. CoRR Nicolas Carion, Gabriel Synnaeve, Alessandro Lazaric, Nicolas Usunier
2019	A	`conf`	Active Exploration in Markov Decision Processes. AISTATS Jean Tarbouriech, Alessandro Lazaric
2019	J	`jnl`	Active Exploration in Markov Decision Processes. CoRR Jean Tarbouriech, Alessandro Lazaric
2019	A*	`conf`	Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs. NeurIPS Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2019	J	`jnl`	Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. CoRR Andrea Zanette, David Brandfonbrener, Matteo Pirotta, Alessandro Lazaric
2019	A*	`conf`	Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret. COLT Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2019	J	`jnl`	Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret. CoRR Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
2019	A*	`conf`	Limiting Extrapolation in Linear Approximate Value Iteration. NeurIPS Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2019	J	`jnl`	No-Regret Exploration in Goal-Oriented Reinforcement Learning. CoRR Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric
2019	A*	`conf`	Regret Bounds for Learning State Representations in Reinforcement Learning. NeurIPS Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, Odalric-Ambrym Maillard
2019	A	`conf`	Rotting bandits are no harder than stochastic ones. AISTATS Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko
2019	—	`conf`	Word-order Biases in Deep-agent Emergent Communication. ACL (1) Rahma Chaabouni, Eugene Kharitonov, Alessandro Lazaric, Emmanuel Dupoux, Marco Baroni
2019	J	`jnl`	Word-order biases in deep-agent emergent communication. CoRR Rahma Chaabouni, Eugene Kharitonov, Alessandro Lazaric, Emmanuel Dupoux, Marco Baroni
2018	J	`jnl`	Distributed Adaptive Sampling for Kernel Matrix Approximation. CoRR Daniele Calandriello, Alessandro Lazaric, Michal Valko
2018	A*	`conf`	Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. ICML Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
2018	J	`jnl`	Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. CoRR Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
2018	J	`jnl`	Exploration Bonus for Regret Minimization in Undiscounted Discrete and Continuous Markov Decision Processes. CoRR Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2018	A*	`conf`	Fighting Boredom in Recommender Systems with Linear Reinforcement Learning. NeurIPS Romain Warlop, Alessandro Lazaric, Jérémie Mary
2018	A*	`conf`	Improved Large-Scale Graph Learning through Ridge Spectral Sparsification. ICML Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric, Michal Valko
2018	A*	`conf`	Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems. ICML Marc Abeille, Alessandro Lazaric
2018	A*	`conf`	Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes. NeurIPS Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2018	J	`jnl`	Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes. CoRR Ronan Fruit, Matteo Pirotta, Alessandro Lazaric
2018	J	`jnl`	Rotting bandits are no harder than stochastic ones. CoRR Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko
2017	A*	`conf`	Active Learning for Accurate Estimation of Linear Models. ICML Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
2017	J	`jnl`	Active Learning for Accurate Estimation of Linear Models. CoRR Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
2017	A	`conf`	Distributed Adaptive Sampling for Kernel Matrix Approximation. AISTATS Daniele Calandriello, Alessandro Lazaric, Michal Valko
2017	—	`conf`	Efficient Second-Order Online Kernel Learning with Adaptive Embedding. NIPS Daniele Calandriello, Alessandro Lazaric, Michal Valko
2017	J	`jnl`	Experimental results : Reinforcement Learning of POMDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2017	A	`conf`	Exploration-Exploitation in MDPs with Options. AISTATS Ronan Fruit, Alessandro Lazaric
2017	J	`jnl`	Exploration-Exploitation in MDPs with Options. CoRR Ronan Fruit, Alessandro Lazaric
2017	A	`conf`	Linear Thompson Sampling Revisited. AISTATS Marc Abeille, Alessandro Lazaric
2017	—	`conf`	Parallel Higher Order Alternating Least Square for Tensor Recommender System. AAAI Workshops Romain Warlop, Alessandro Lazaric, Jérémie Mary
2017	—	`conf`	Regret Minimization in MDPs with Options without Prior Knowledge. NIPS Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Emma Brunskill
2017	A*	`conf`	Second-Order Kernel Online Convex Optimization with Adaptive Sketching. ICML Daniele Calandriello, Alessandro Lazaric, Michal Valko
2017	J	`jnl`	Second-Order Kernel Online Convex Optimization with Adaptive Sketching. CoRR Daniele Calandriello, Alessandro Lazaric, Michal Valko
2017	A	`conf`	Thompson Sampling for Linear-Quadratic Control Problems. AISTATS Marc Abeille, Alessandro Lazaric
2017	A	`conf`	Trading off Rewards and Errors in Multi-Armed Bandits. AISTATS Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu
2016	J	`jnl`	Analysis of Classification-based Policy Iteration Algorithms. J. Mach. Learn. Res. Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2016	J	`jnl`	Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting. CoRR Daniele Calandriello, Alessandro Lazaric, Michal Valko
2016	A	`conf`	Analysis of Nyström method with sequential ridge leverage scores. UAI Daniele Calandriello, Alessandro Lazaric, Michal Valko
2016	A	`conf`	Improved Learning Complexity in Combinatorial Pure Exploration Bandits. AISTATS Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett
2016	J	`jnl`	Incremental Spectral Sparsification for Large-Scale Graph-Based Semi-Supervised Learning. CoRR Daniele Calandriello, Alessandro Lazaric, Michal Valko, Ioannis Koutis
2016	J	`jnl`	Linear Thompson Sampling Revisited. CoRR Marc Abeille, Alessandro Lazaric
2016	A*	`conf`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of Contextual MDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of POMDP's using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	A*	`conf`	Reinforcement Learning of POMDPs using Spectral Methods. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2015	A*	`conf`	Direct Policy Iteration with Demonstrations. IJCAI Jessica Chemali, Alessandro Lazaric
2015	A*	`conf`	Maximum Entropy Semi-Supervised Inverse Reinforcement Learning. IJCAI Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh
2015	J	`jnl`	Sparse multi-task reinforcement learning. Intelligenza Artificiale Daniele Calandriello, Alessandro Lazaric, Marcello Restelli
2015	B	`conf`	The replacement bootstrap for dependent data. ISIT Amir Sani, Alessandro Lazaric, Daniil Ryabko
2015	J	`jnl`	Truthful learning mechanisms for multi-slot sponsored search auctions with externalities. Artif. Intell. Nicola Gatti, Alessandro Lazaric, Marco Rocco, Francesco Trovò
2015	J	`jnl`	Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits. CoRR Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer, András Antos
2014	—	`conf`	Best-Arm Identification in Linear Bandits. NIPS Marta Soare, Alessandro Lazaric, Rémi Munos
2014	J	`jnl`	Best-Arm Identification in Linear Bandits. CoRR Marta Soare, Alessandro Lazaric, Rémi Munos
2014	—	`conf`	Exploiting easy data in online optimization. NIPS Amir Sani, Gergely Neu, Alessandro Lazaric
2014	A*	`conf`	Online Stochastic Optimization under Correlated Bandit Feedback. ICML Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2014	—	`conf`	Sparse Multi-Task Reinforcement Learning. NIPS Daniele Calandriello, Alessandro Lazaric, Marcello Restelli
2014	J	`jnl`	Stochastic Optimization of a Locally Smooth Function under Correlated Bandit Feedback. CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2014	J	`jnl`	Truthful Learning Mechanisms for Multi-Slot Sponsored Search Auctions with Externalities. CoRR Nicola Gatti, Alessandro Lazaric, Marco Rocco, Francesco Trovò
2013	J	`jnl`	Regret Bounds for Reinforcement Learning with Policy Advice CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	—	`conf`	Regret Bounds for Reinforcement Learning with Policy Advice. ECML/PKDD (1) Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	J	`jnl`	Risk-Aversion in Multi-armed Bandits CoRR Amir Sani, Alessandro Lazaric, Rémi Munos
2013	—	`conf`	Sequential Transfer in Multi-armed Bandit with Finite Set of Models. NIPS Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	J	`jnl`	Sequential Transfer in Multi-armed Bandit with Finite Set of Models. CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2012	A*	`conf`	A Dantzig Selector Approach to Temporal Difference Learning. ICML Matthieu Geist, Bruno Scherrer, Alessandro Lazaric, Mohammad Ghavamzadeh
2012	A*	`conf`	A truthful learning mechanism for contextual multi-slot sponsored search auctions with externalities. EC Nicola Gatti, Alessandro Lazaric, Francesco Trovò
2012	A	`conf`	A truthful learning mechanism for multi-slot sponsored search auctions with externalities. AAMAS Nicola Gatti, Alessandro Lazaric, Francesco Trovò
2012	—	`conf`	Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric
2012	A*	`conf`	Conservative and Greedy Approaches to Classification-Based Policy Iteration. AAAI Mohammad Ghavamzadeh, Alessandro Lazaric
2012	J	`jnl`	Finite-sample analysis of least-squares policy iteration. J. Mach. Learn. Res. Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2012	J	`jnl`	Learning with stochastic inputs and adversarial outputs. J. Comput. Syst. Sci. Alessandro Lazaric, Rémi Munos
2012	—	`ch.`	Least-Squares Methods for Policy Iteration. Reinforcement Learning Lucian Busoniu, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Robert Babuska, Bart De Schutter
2012	—	`conf`	Risk-Aversion in Multi-armed Bandits. NIPS Amir Sani, Alessandro Lazaric, Rémi Munos
2012	—	`conf`	Semi-Supervised Apprenticeship Learning. EWRL Michal Valko, Mohammad Ghavamzadeh, Alessandro Lazaric
2012	—	`ch.`	Transfer in Reinforcement Learning: A Framework and a Survey. Reinforcement Learning Alessandro Lazaric
2011	A*	`conf`	Classification-based Policy Iteration with a Critic. ICML Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Bruno Scherrer
2011	A*	`conf`	Finite-Sample Analysis of Lasso-TD. ICML Mohammad Ghavamzadeh, Alessandro Lazaric, Rémi Munos, Matthew W. Hoffman
2011	—	`conf`	Multi-Bandit Best Arm Identification. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck
2011	—	`conf`	Regularized Least Squares Temporal Difference Learning with Nested ℓ2 and ℓ1 Penalization. EWRL Matthew W. Hoffman, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2011	J	`jnl`	Transfer from Multiple MDPs CoRR Alessandro Lazaric, Marcello Restelli
2011	—	`conf`	Transfer from Multiple MDPs. NIPS Alessandro Lazaric, Marcello Restelli
2011	B	`conf`	Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits. ALT Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer
2010	A*	`conf`	Analysis of a Classification-based Policy Iteration Algorithm. ICML Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2010	A*	`conf`	Bayesian Multi-Task Reinforcement Learning. ICML Alessandro Lazaric, Mohammad Ghavamzadeh
2010	A*	`conf`	Finite-Sample Analysis of LSTD. ICML Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos
2010	C	`conf`	Finite-sample Analysis of Bellman Residual Minimization. ACML Odalric-Ambrym Maillard, Rémi Munos, Alessandro Lazaric, Mohammad Ghavamzadeh
2010	—	`conf`	LSTD with Random Projections. NIPS Mohammad Ghavamzadeh, Alessandro Lazaric, Odalric-Ambrym Maillard, Rémi Munos
2009	A*	`conf`	Hybrid Stochastic-Adversarial On-line Learning. COLT Alessandro Lazaric, Rémi Munos
2009	J	`jnl`	Reinforcement distribution in fuzzy Q-learning. Fuzzy Sets Syst. Andrea Bonarini, Alessandro Lazaric, Francesco Montrone, Marcello Restelli
2009	A*	`conf`	Workshop summary: On-line learning with limited feedback. ICML Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári
2008	—	`conf`	Batch Reinforcement Learning for Controlling a Mobile Wheeled Pendulum Robot. IFIP AI Andrea Bonarini, Claudio Caccia, Alessandro Lazaric, Marcello Restelli
2008	—	`conf`	Improving Batch Reinforcement Learning Performance through Transfer of Samples. STAIRS Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
2008	—	`conf`	On the usefulness of opponent modeling: the Kuhn Poker case study. AAMAS (3) Alessandro Lazaric, Mario Quaresimale, Marcello Restelli
2008	—	`conf`	Towards Automated Bargaining in Electronic Markets: A Partially Two-Sided Competition Model. AMEC/TADA Nicola Gatti, Alessandro Lazaric, Marcello Restelli
2008	A*	`conf`	Transfer of samples in batch reinforcement learning. ICML Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
2008	—	`conf`	Transfer of task representation in reinforcement learning using policy-based proto-value functions. AAMAS (3) Eliseo Ferrante, Alessandro Lazaric, Marcello Restelli
2007	—	`conf`	Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game. Adaptive Agents and Multi-Agents Systems Alessandro Lazaric, Enrique Munoz de Cote, Fabio Dercole, Marcello Restelli
2007	—	`conf`	Piecewise constant reinforcement learning for robotic applications. ICINCO-ICSO Andrea Bonarini, Alessandro Lazaric, Marcello Restelli
2007	—	`conf`	Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions. AI*IA Andrea Bonarini, Alessandro Lazaric, Marcello Restelli
2007	—	`conf`	Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods. NIPS Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
2007	A	`conf`	Reinforcement learning in extensive form games with incomplete information: the bargaining case study. AAMAS Alessandro Lazaric, Enrique Munoz de Cote, Nicola Gatti
2006	—	`conf`	Incremental Skill Acquisition for Self-motivated Learning Animats. SAB Andrea Bonarini, Alessandro Lazaric, Marcello Restelli
2006	A	`conf`	Learning to cooperate in multi-agent social dilemmas. AAMAS Enrique Munoz de Cote, Alessandro Lazaric, Marcello Restelli