Alessandro Lazaric

Temporal Difference Flows ICML 2025 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models ICLR 2025 Fast Imitation via Behavior Foundation Models ICLR 2024 Simple Ingredients for Offline Reinforcement Learning ICML 2024 Contextual bandits with concave rewards, and an application to fair ranking ICLR 2023 Layered State Discovery for Incremental Autonomous Exploration ICML 2023 Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies ICLR 2023 On the Complexity of Representation Learning in Contextual Linear Bandits AISTATS 2023 Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path ALT 2023 Adaptive Multi-Goal Exploration AISTATS 2022 A general sample complexity analysis of vanilla policy gradient AISTATS 2022 A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning ICLR 2022 Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching ICLR 2022 Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping CoRL 2022 Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning ICLR 2022 Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees NeurIPS 2022 Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times ICML 2022 Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL UAI 2022 Top K Ranking for Multi-Armed Bandit with Noisy Evaluations AISTATS 2022 A Provably Efficient Sample Collection Strategy for Reinforcement Learning NeurIPS 2021 Leveraging Good Representations in Linear Contextual Bandits ICML 2021 Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection NeurIPS 2021 Reinforcement Learning with Prototypical Representations ICML 2021 Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model ALT 2021 Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret NeurIPS 2021 Active Model Estimation in Markov Decision Processes UAI 2020 Adversarial Attacks on Linear Contextual Bandits NeurIPS 2020 An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NeurIPS 2020 A Novel Confidence-Based Algorithm for Structured Bandits AISTATS 2020 A single algorithm for both restless and rested rotting bandits AISTATS 2020 Conservative Exploration in Reinforcement Learning AISTATS 2020 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation ICML 2020 Frequentist Regret Bounds for Randomized Least-Squares Value Iteration AISTATS 2020 Improved Algorithms for Conservative Exploration in Bandits AAAI 2020 Improved Sample Complexity for Incremental Autonomous Exploration in MDPs NeurIPS 2020 Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020 Meta-learning with Stochastic Linear Bandits ICML 2020 Near-linear time Gaussian process optimization with adaptive batching and resparsification ICML 2020 No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020 Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration NeurIPS 2020 Active Exploration in Markov Decision Processes AISTATS 2019 A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning NeurIPS 2019 Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs NeurIPS 2019 Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret COLT 2019 Limiting Extrapolation in Linear Approximate Value Iteration NeurIPS 2019 Regret Bounds for Learning State Representations in Reinforcement Learning NeurIPS 2019 Rotting bandits are no harder than stochastic ones AISTATS 2019 Word-order Biases in Deep-agent Emergent Communication ACL 2019 Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning ICML 2018 Fighting Boredom in Recommender Systems with Linear Reinforcement Learning NeurIPS 2018 Improved large-scale graph learning through ridge spectral sparsification ICML 2018 Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems ICML 2018 Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NeurIPS 2018 Active Learning for Accurate Estimation of Linear Models ICML 2017 Distributed Adaptive Sampling for Kernel Matrix Approximation AISTATS 2017 Efficient Second-Order Online Kernel Learning with Adaptive Embedding NeurIPS 2017 Exploration-Exploitation in MDPs with Options AISTATS 2017 Linear Thompson Sampling Revisited AISTATS 2017 Regret Minimization in MDPs with Options without Prior Knowledge NeurIPS 2017 Second-Order Kernel Online Convex Optimization with Adaptive Sketching ICML 2017 Thompson Sampling for Linear-Quadratic Control Problems AISTATS 2017 Trading off Rewards and Errors in Multi-Armed Bandits AISTATS 2017 Analysis of Classification-based Policy Iteration Algorithms JMLR 2016 Improved Learning Complexity in Combinatorial Pure Exploration Bandits AISTATS 2016 Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies COLT 2016 Reinforcement Learning of POMDPs using Spectral Methods COLT 2016 Direct Policy Iteration with Demonstrations IJCAI 2015 Maximum Entropy Semi-Supervised Inverse Reinforcement Learning IJCAI 2015 Best-Arm Identification in Linear Bandits NeurIPS 2014 Exploiting easy data in online optimization NeurIPS 2014 Online Stochastic Optimization under Correlated Bandit Feedback ICML 2014 Sparse Multi-Task Reinforcement Learning NeurIPS 2014 Sequential Transfer in Multi-armed Bandit with Finite Set of Models NeurIPS 2013 Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence NeurIPS 2012 Finite-Sample Analysis of Least-Squares Policy Iteration JMLR 2012 Risk-Aversion in Multi-armed Bandits NeurIPS 2012 Multi-Bandit Best Arm Identification NeurIPS 2011 Transfer from Multiple MDPs NeurIPS 2011 Finite-sample Analysis of Bellman Residual Minimization ACML 2010 LSTD with Random Projections NeurIPS 2010 Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods NeurIPS 2007