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Matteo Pirotta

44 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (8) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (15) πŸƒ Academic Marathon (12) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (30) πŸ† Keyword Champion πŸ† Grand Slam πŸ”¬ Deep Specialist (15) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (10) πŸ—ƒοΈ Keyword Collector (147) πŸ’Ž Century Club (44)

Conferences

NIPS (15) ICML (11) AISTATS (7) ICLR (4) ALT (3) JMLR (2) AAAI (1) UAI (1)

Top co-authors

Alessandro Lazaric (30) Marcello Restelli (12) Andrea Tirinzoni (12) Evrard Garcelon (9) Michal Valko (8) Jean Tarbouriech (8) Ahmed Touati (5) Ronan Fruit (5) Matteo Papini (5) Omar Darwiche Domingues (3)

Research topics

Differential Privacy (1)

Keywords

regret bound (15) markov decision process (13) reinforcement learning (11) sample complexity (6) contextual bandit (5) regret minimization (5) policy gradient (4) representation learning (4) optimistic algorithm (3) function approximation (3) online learning (3) contextual linear bandit (3) stochastic shortest path (3) linear bandit (2) step size optimization (2) policy iteration (2) value iteration (2) autonomous exploration (2) exploration-exploitation tradeoff (2) multi-armed bandit (2)

Papers

Temporal Difference Flows ICML 2025
Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models ICLR 2025
Simple Ingredients for Offline Reinforcement Learning ICML 2024
Fast Imitation via Behavior Foundation Models ICLR 2024
Contextual bandits with concave rewards, and an application to fair ranking ICLR 2023
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path ALT 2023
Layered State Discovery for Incremental Autonomous Exploration ICML 2023
On the Complexity of Representation Learning in Contextual Linear Bandits AISTATS 2023
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning ICLR 2022
Encrypted Linear Contextual Bandit AISTATS 2022
Top K Ranking for Multi-Armed Bandit with Noisy Evaluations AISTATS 2022
Adaptive Multi-Goal Exploration AISTATS 2022
Privacy Amplification via Shuffling for Linear Contextual Bandits ALT 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees NIPS 2022
Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model ALT 2021
Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021
Gaussian Approximation for Bias Reduction in Q-Learning JMLR 2021
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach JMLR 2021
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret NIPS 2021
A Provably Efficient Sample Collection Strategy for Reinforcement Learning NIPS 2021
Local Differential Privacy for Regret Minimization in Reinforcement Learning NIPS 2021
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection NIPS 2021
Leveraging Good Representations in Linear Contextual Bandits ICML 2021
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021
Active Model Estimation in Markov Decision Processes UAI 2020
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NIPS 2020
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs NIPS 2020
Adversarial Attacks on Linear Contextual Bandits NIPS 2020
Improved Algorithms for Conservative Exploration in Bandits AAAI 2020
Conservative Exploration in Reinforcement Learning AISTATS 2020
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration AISTATS 2020
No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020
Regret Bounds for Learning State Representations in Reinforcement Learning NIPS 2019
Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs NIPS 2019
Importance Weighted Transfer of Samples in Reinforcement Learning ICML 2018
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning ICML 2018
Stochastic Variance-Reduced Policy Gradient ICML 2018
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NIPS 2018
Boosted Fitted Q-Iteration ICML 2017
Adaptive Batch Size for Safe Policy Gradients NIPS 2017
Compatible Reward Inverse Reinforcement Learning NIPS 2017
Regret Minimization in MDPs with Options without Prior Knowledge NIPS 2017
Adaptive Step-Size for Policy Gradient Methods NIPS 2013
Safe Policy Iteration ICML 2013