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*: Equal contribution

Preprints

  1. W. Xiong, C. Shi, J. Shen, A. Rosenberg, Z. Qin, D. Calandriello, M. Khalman, R. Joshi, B. Piot, M. Saleh, C. Jin, T. Zhang, and T. Liu, “Building Math Agents with Multi-Turn Iterative Preference Learning”, Sep. 2024

Journal Papers

  1. [TMLR] C. Shi, R. Zhou, K. Yang, and C. Shen, “Harnessing the Power of Federated Learning in Federated Contextual Bandits”, Transactions on Machine Learning Research, July 2024

    1. Also appears in NeurIPs 2023 Workshop on Multi-Agent Security, Dec. 2023

  2. [IEEE TWC] K. Yang, C. Shi, C. Shen, J. Yang, S. Yeh, and J. Sydir, “Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets”, IEEE Transactions on Wireless Communications, to appear, May 2024

  3. [IEEE TSP] C. Shi, W. Xiong, C. Shen, and J. Yang, “Reward Teaching for Federated Multi-Armed Bandits”, IEEE Transactions on Signal Processing, vol.71, pp.4407-4422, Nov. 2023

  4. [IEEE TSP] C. Shi and C. Shen, “Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions”, IEEE Transactions on Signal Processing, vol. 69, pp. 4385–4402, July 2021

  5. [IEEE JSAIT] C. Shi and C. Shen, “On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications”, IEEE Journal on Selected Areas in Information Theory, vol. 2, no. 2, pp. 515-533, June 2021

Conference Papers

  1. [NeurIPS 2024] C. Shi*, K. Yang*, Z. Chen, J. Li, J. Yang, and C. Shen, “Efficient Prompt Optimization Through the Lens of Best Arm Identification”, The 38th Annual Conference on Neural Information Processing Systems, Dec. 2024

    1. Also appears in ICLR 2024 Workshop on Mathematical and Empirical Understanding of Foundation Models, May 2024

  2. [NeurIPS 2024] C. Shi, K. Yang, J. Yang, and C. Shen, “Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models”, The 38th Annual Conference on Neural Information Processing Systems, Dec. 2024

    1. Also appears in ICLR 2024 Workshop on Generative Models for Decision Making, May 2024

  3. [NeurIPS 2024] S. Wang, Z. Chen, C. Shi, C. Shen, and J. Li, “Mixture of Demonstrations for In-Context Learning”, The 38th Annual Conference on Neural Information Processing Systems, Dec. 2024

  4. [ICML 2023] C. Shi, W. Xiong, C. Shen, and J. Yang, “Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources”, The 40th International Conference on Machine Learning, June 2023

  5. [ISIT 2023] C. Shi, C. Shen, and N. D. Sidiropoulos, “On High-Dimensional and Low-Rank Tensor Bandits”, 2023 IEEE International Symposium on Information Theory, June 2023

  6. [ISIT 2023] C. Shi, W. Xiong, C. Shen, and J. Yang, “Reward Teaching for Federated Multi-Armed Bandits”, 2023 IEEE International Symposium on Information Theory, June 2023

  7. [CISS 2023] K. Yang, C. Shi, and C. Shen, “Teaching Reinforcement Learning Agents via Reinforcement Learning”, 57th Annual Conference on Information Sciences and Systems, March 2023 (Invited Paper)

  8. [ICLR 2023] W. Xiong, H. Zhong, C. Shi, C. Shen, L. Wang, and T. Zhang, “Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game”, The Eleventh International Conference on Learning Representations, May 2023

  9. [ICML 2022] W. Xiong, H. Zhong, C. Shi, C. Shen, and T. Zhang, “A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games”, The 39th International Conference on Machine Learning, July 2022

    1. Also appears in ICLR 2022 Workshop on Gamification and Multiagent Solutions, April 2022

  10. [NeurIPS 2021] C. Shi, W. Xiong, C. Shen, and J. Yang, “Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization”, The 35th Conference on Neural Information Processing Systems, Dec. 2021

  11. [NeurIPS 2021] C. Shi, H. Xu, W. Xiong, and C. Shen, “(Almost) Free Incentivized Exploration from Decentralized Learning Agents”, The 35th Conference on Neural Information Processing Systems, Dec. 2021

  12. [ISIT 2021] C. Shi and C. Shen, “An Attackability Perspective on No-Sensing Adversarial Multi-player Multi-armed Bandits”, 2021 IEEE International Symposium on Information Theory, July 2021

  13. [AISTATS 2021] C. Shi, C. Shen, and J. Yang, “Federated Multi-armed Bandits with Personalization”, The 24th International Conference on Artificial Intelligence and Statistics, Apr. 2021 (Oral Presentation, 48/1527 = 3%)

  14. [AAAI 2021] C. Shi and C. Shen, “Federated Multi-Armed Bandits”, The 35th AAAI Conference on Artificial Intelligence, Feb. 2021

  15. [AISTATS 2020] C. Shi, W. Xiong, C. Shen, and J. Yang, “Decentralized Multi-player Multi-armed Bandits with No Collision Information”, The 23rd International Conference on Artificial Intelligence and Statistics, Aug. 2020

  16. [Globecom 2019] C. Shi, L. Chen, C. Shen, L. Song, and J. Xu, “Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning”, IEEE Global Communications Conference, Dec. 2019