Chen-Yu Wei
Orcid: 0000-0001-8735-4773
According to our database1,
Chen-Yu Wei
authored at least 50 papers
between 2016 and 2024.
Collaborative distances:
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Bibliography
2024
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the International Conference on Algorithmic Learning Theory, 2023
2022
CoRR, 2022
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022
2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games.
Proceedings of the Conference on Learning Theory, 2021
Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach.
Proceedings of the Conference on Learning Theory, 2021
Proceedings of the Conference on Learning Theory, 2021
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition.
Proceedings of the Conference on Learning Theory, 2021
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds.
Proceedings of the Algorithmic Learning Theory, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Conference on Learning Theory, 2020
2019
Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator.
CoRR, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case.
Proceedings of the 36th International Conference on Machine Learning, 2019
A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free.
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the Conference on Learning Theory, 2019
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information.
Proceedings of the Conference on Learning Theory, 2019
2018
Multi-Cell Cooperative Scheduling for Network Utility Maximization With User Equipment Side Interference Cancellation.
IEEE Trans. Wirel. Commun., 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Adaptive measurement for energy efficient mobility management in ultra-dense small cell networks.
Proceedings of the 2016 IEEE International Conference on Communications, 2016