← Authors

Andrea Tirinzoni

25 papers · 2018–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (38) 🀝 Dynamic Duo (12) πŸ† Keyword Champion (3) πŸ† Grand Slam πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (93) πŸ’Ž Century Club (25) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (8)

Conferences

NIPS (8) ICML (7) AISTATS (3) ALT (2) ICLR (2) AAAI (1) COLT (1) IJCAI (1)

Top co-authors

Alessandro Lazaric (12) Matteo Pirotta (12) Marcello Restelli (11) Ahmed Touati (5) Matteo Papini (4) Emilie Kaufmann (3) Aymen Al-Marjani (2) RΓ©my Degenne (2) Alberto Maria Metelli (2) Jesse Farebrother (2)

Keywords

sample complexity (7) representation learning (4) markov decision process (4) transfer learning (4) regret bound (4) pac reinforcement learning (3) reinforcement learning (3) constant regret (2) contextual linear bandit (2) policy search (2) contextual bandit (2) policy gradient (2) optimistic algorithm (2) exploration policy (2) variational inference (2) multi-armed bandit (2) instance-dependent bound (2) inverse reinforcement learning (1) adaptive sampling (1) policy optimization (1)

Papers

Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models ICLR 2025
Temporal Difference Flows ICML 2025
Simple Ingredients for Offline Reinforcement Learning ICML 2024
Fast Imitation via Behavior Foundation Models ICLR 2024
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path ALT 2023
Optimistic PAC Reinforcement Learning: the Instance-Dependent View ALT 2023
Active Coverage for PAC Reinforcement Learning COLT 2023
Layered State Discovery for Incremental Autonomous Exploration ICML 2023
On the Complexity of Representation Learning in Contextual Linear Bandits AISTATS 2023
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs NIPS 2022
On Elimination Strategies for Bandit Fixed-Confidence Identification NIPS 2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees NIPS 2022
Meta-Reinforcement Learning by Tracking Task Non-stationarity IJCAI 2021
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection NIPS 2021
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification NIPS 2021
Leveraging Good Representations in Linear Contextual Bandits ICML 2021
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions AISTATS 2020
Sequential Transfer in Reinforcement Learning with a Generative Model ICML 2020
Gradient-Aware Model-Based Policy Search AAAI 2020
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NIPS 2020
A Novel Confidence-Based Algorithm for Structured Bandits AISTATS 2020
Transfer of Samples in Policy Search via Multiple Importance Sampling ICML 2019
Importance Weighted Transfer of Samples in Reinforcement Learning ICML 2018
Transfer of Value Functions via Variational Methods NIPS 2018
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes NIPS 2018