Andrea Tirinzoni
25 papers · 2018–2025 · 8 conferences · across top CS/AI conferences
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Conferences
NIPS (8)
ICML (7)
AISTATS (3)
ALT (2)
ICLR (2)
AAAI (1)
COLT (1)
IJCAI (1)
Top co-authors
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