Andrea Zanette

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 32

Top Topics

Approximate Value Iteration

Reinforcement Learning

Top Venues

Publications

Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. CoRR (2024)
Ruiqi Zhang, Yuexiang Zhai, Andrea Zanette
Is Offline Decision Making Possible with Only Few Samples? Reliable Decisions in Data-Starved Bandits via Trust Region Enhancement. CoRR (2024)
Andrea Zanette
When is Realizability Sufficient for Off-Policy Reinforcement Learning? ICML (2023)
Ruiqi Zhang, Andrea Zanette
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data. CoRR (2023)
Ruiqi Zhang, Andrea Zanette
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data. NeurIPS (2023)
Andrea Zanette, Martin J. Wainwright
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning. CoRR (2022)
Andrea Zanette, Martin J. Wainwright
Bellman Residual Orthogonalization for Offline Reinforcement Learning. NeurIPS (2022)
Andrea Zanette
When is Realizability Sufficient for Off-Policy Reinforcement Learning? CoRR (2022)
Andrea Zanette, Martin J. Wainwright
Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning. ICML (2022)
Andrea Zanette, Martin J. Wainwright
Bellman Residual Orthogonalization for Offline Reinforcement Learning. CoRR (2022)
Andrea Zanette, Kefan Dong, Jonathan N. Lee, Emma Brunskill
Design of Experiments for Stochastic Contextual Linear Bandits. CoRR (2021)
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. CoRR (2021)
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. COLT (2021)
Andrea Zanette, Martin J. Wainwright, Emma Brunskill
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. CoRR (2021)
Andrea Zanette
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL. ICML (2021)
Andrea Zanette, Kefan Dong, Jonathan N. Lee, Emma Brunskill
Design of Experiments for Stochastic Contextual Linear Bandits. NeurIPS (2021)
Andrea Zanette, Martin J. Wainwright, Emma Brunskill
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. NeurIPS (2021)
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Learning Near Optimal Policies with Low Inherent Bellman Error. ICML (2020)
Andrea Zanette
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL. CoRR (2020)
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. CoRR (2020)
Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. AISTATS (2020)
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. NeurIPS (2020)
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Learning Near Optimal Policies with Low Inherent Bellman Error. CoRR (2020)
Andrea Zanette, Emma Brunskill
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs. CoRR (2019)
Andrea Zanette, Mykel J. Kochenderfer, Emma Brunskill
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model. NeurIPS (2019)
Andrea Zanette, Emma Brunskill
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds. ICML (2019)
Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
Limiting Extrapolation in Linear Approximate Value Iteration. NeurIPS (2019)
Andrea Zanette, Emma Brunskill
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds. CoRR (2019)
Andrea Zanette, David Brandfonbrener, Matteo Pirotta, Alessandro Lazaric
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. CoRR (2019)
Andrea Zanette, Emma Brunskill
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs. ICML (2018)
Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer
Robust Super-Level Set Estimation using Gaussian Processes. CoRR (2018)
Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer
Robust Super-Level Set Estimation Using Gaussian Processes. ECML/PKDD (2) (2018)