Chengshuai Shi

According to our database, Chengshuai Shi authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Best Arm Identification for Prompt Learning under a Limited Budget.

Chengshuai Shi, Kun Yang, Jing Yang, Cong Shen

CoRR, 2024

2023

Reward Teaching for Federated Multiarmed Bandits.

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

IEEE Trans. Signal Process., 2023

Harnessing the Power of Federated Learning in Federated Contextual Bandits.

Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen

CoRR, 2023

Reward Teaching for Federated Multi-armed Bandits.

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

Proceedings of the IEEE International Symposium on Information Theory, 2023

On High-dimensional and Low-rank Tensor Bandits.

Chengshuai Shi, Cong Shen, Nicholas D. Sidiropoulos

Proceedings of the IEEE International Symposium on Information Theory, 2023

Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources.

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

Proceedings of the International Conference on Machine Learning, 2023

Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game.

Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Teaching Reinforcement Learning Agents via Reinforcement Learning.

Kun Yang, Chengshuai Shi, Cong Shen

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

2022

A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games.

Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

Proceedings of the International Conference on Machine Learning, 2022

2021

Multi-Player Multi-Armed Bandits With Collision-Dependent Reward Distributions.

Chengshuai Shi, Cong Shen

IEEE Trans. Signal Process., 2021

On No-Sensing Adversarial Multi-Player Multi-Armed Bandits With Collision Communications.

Chengshuai Shi, Cong Shen

IEEE J. Sel. Areas Inf. Theory, 2021

(Almost) Free Incentivized Exploration from Decentralized Learning Agents.

Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen

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

Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization.

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

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

An Attackability Perspective on No-Sensing Adversarial Multi-player Multi-armed Bandits.

Chengshuai Shi, Cong Shen

Proceedings of the IEEE International Symposium on Information Theory, 2021

Federated Multi-armed Bandits with Personalization.

Chengshuai Shi, Cong Shen, Jing Yang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Federated Multi-Armed Bandits.

Chengshuai Shi, Cong Shen

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Decentralized Multi-player Multi-armed Bandits with No Collision Information.

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning.

Chengshuai Shi, Lixing Chen, Cong Shen, Linqi Song, Jie Xu

Proceedings of the 2019 IEEE Global Communications Conference, 2019