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Andrea Zanette
Andrea Zanette
Assistant Professor, Carnegie Mellon University
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
Tighter problem-dependent regret bounds in reinforcement learning without domain knowledge using value function bounds
A Zanette, E Brunskill
International Conference on Machine Learning, 7304-7312, 2019
2832019
Learning near optimal policies with low inherent bellman error
A Zanette, A Lazaric, M Kochenderfer, E Brunskill
International Conference on Machine Learning, 10978-10989, 2020
2122020
Frequentist regret bounds for randomized least-squares value iteration
A Zanette, D Brandfonbrener, E Brunskill, M Pirotta, A Lazaric
International Conference on Artificial Intelligence and Statistics, 1954-1964, 2020
1332020
Provable benefits of actor-critic methods for offline reinforcement learning
A Zanette, MJ Wainwright, E Brunskill
Advances in neural information processing systems 34, 13626-13640, 2021
1072021
Exponential lower bounds for batch reinforcement learning: Batch rl can be exponentially harder than online rl
A Zanette
International Conference on Machine Learning, 12287-12297, 2021
842021
Provably efficient reward-agnostic navigation with linear value iteration
A Zanette, A Lazaric, MJ Kochenderfer, E Brunskill
Advances in Neural Information Processing Systems 33, 11756-11766, 2020
572020
Cautiously optimistic policy optimization and exploration with linear function approximation
A Zanette, CA Cheng, A Agarwal
Conference on Learning Theory, 4473-4525, 2021
532021
Almost horizon-free structure-aware best policy identification with a generative model
A Zanette, MJ Kochenderfer, E Brunskill
Advances in Neural Information Processing Systems 32, 2019
382019
Limiting extrapolation in linear approximate value iteration
A Zanette, A Lazaric, MJ Kochenderfer, E Brunskill
Advances in Neural Information Processing Systems 32, 2019
372019
Robust super-level set estimation using Gaussian processes
A Zanette, J Zhang, MJ Kochenderfer
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
332019
Design of experiments for stochastic contextual linear bandits
A Zanette, K Dong, JN Lee, E Brunskill
Advances in Neural Information Processing Systems 34, 22720-22731, 2021
222021
Problem dependent reinforcement learning bounds which can identify bandit structure in mdps
A Zanette, E Brunskill
International Conference on Machine Learning, 5747-5755, 2018
212018
When is realizability sufficient for off-policy reinforcement learning?
A Zanette
International Conference on Machine Learning, 40637-40668, 2023
102023
Bellman residual orthogonalization for offline reinforcement learning
A Zanette, MJ Wainwright
Advances in Neural Information Processing Systems 35, 3137-3151, 2022
102022
Information directed reinforcement learning
A Zanette, R Sarkar
Tech. Rep., Technical report, Technical report, 2017
72017
Stabilizing q-learning with linear architectures for provable efficient learning
A Zanette, M Wainwright
International Conference on Machine Learning, 25920-25954, 2022
62022
Policy finetuning in reinforcement learning via design of experiments using offline data
R Zhang, A Zanette
Advances in Neural Information Processing Systems 36, 2024
22024
Enriching the finite element method with meshfree particles in structural mechanics
A Zanette, M Ferronato, C Janna
International Journal for Numerical Methods in Engineering 110 (7), 675-700, 2017
22017
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
Y Zhou, A Zanette, J Pan, S Levine, A Kumar
arXiv preprint arXiv:2402.19446, 2024
2024
Is Offline Decision Making Possible with Only Few Samples? Reliable Decisions in Data-Starved Bandits via Trust Region Enhancement
R Zhang, Y Zhai, A Zanette
arXiv preprint arXiv:2402.15703, 2024
2024
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