Jiafan He

CoRR, 2024

Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption.

[BibT_eX]

[DOI]

CoRR, 2024

Emergency Localization for Mobile Ground Users: An Adaptive UAV Trajectory Planning Method.

[BibT_eX]

[DOI]

CoRR, 2024

2023

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation.

[BibT_eX]

[DOI]

Heyang Zhao

CoRR, 2023

Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs.

[BibT_eX]

[DOI]

CoRR, 2023

Attitude Synchronization of Heterogenous Flexible Spacecrafts by Measurement-Based Feedback With Disturbance Suppression.

[BibT_eX]

[DOI]

IEEE Access, 2023

Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension.

[BibT_eX]

[DOI]

Yue Wu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency.

[BibT_eX]

[DOI]

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Cooperative Global Robust Practical Output Regulation of Nonlinear Lower Triangular Multiagent Systems via Event-Triggered Control.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2022

Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds.

[BibT_eX]

[DOI]

CoRR, 2022

Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Stochastic Shortest Path with Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs.

[BibT_eX]

[DOI]

Yuanzhou Chen

Proceedings of the International Conference on Machine Learning, 2022

Accurate Decision-Making Method for Air Combat Pilots Based on Data-Driven.

[BibT_eX]

[DOI]

Proceedings of the Data Mining and Big Data - 7th International Conference, 2022

Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes.

[BibT_eX]

[DOI]

Chonghua Liao

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Provably Efficient Representation Learning in Low-rank Markov Decision Processes.

[BibT_eX]

[DOI]

CoRR, 2021

Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation.

[BibT_eX]

[DOI]

CoRR, 2021

Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Logarithmic Regret for Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Minimax Optimal Reinforcement Learning for Discounted MDPs.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Achieving a Fairer Future by Changing the Past.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Robust Attitude Regulation of Uncertain Spacecraft with Flexible Appendages.

[BibT_eX]

[DOI]