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Creators/Authors contains: "Peng, Binghui"

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  1. ; ( , Proceedings of the 64th IEEE Symposium on Foundations of Computer Science)
  2. ; ( , ACM)
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  3. ; ( , Games and Economic Behavior)
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  4. ; ( , Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA))
    We provide the first sub-linear space and sub-linear regret algorithm for online learning with expert advice (against an oblivious adversary), addressing an open question raised recently by Srinivas, Woodruff, Xu and Zhou (STOC 2022). We also demonstrate a separation between oblivious and (strong) adaptive adversaries by proving a linear memory lower bound of any sub-linear regret algorithm against an adaptive adversary. Our algorithm is based on a novel pool selection procedure that bypasses the traditional wisdom of leader selection for online learning, and a generic reduction that transforms any weakly sub-linear regret o(T) algorithm to T1-α regret algorithm, which may be of independent interest. Our lower bound utilizes the connection of no-regret learning and equilibrium computation in zero-sum games, leading to a proof of a strong lower bound against an adaptive adversary. 
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  5. ; ; ( , In Proceedings of the 63rd IEEE Symposium on Foundations of Computer Science (FOCS))
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  6. ; ( , Proceedings of the 54th ACM Symposium on Theory of Computing (STOC 22'))
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  7. ; ; ; ( , Annual ACM-SIAM Symposium on Discrete Algorithms)
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  8. ; ( , ACM Conference on Economics and Computation)
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  9. ; ; ; ( , Annual Meeting of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing)
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  10. ; ( , Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020))
    null (Ed.)
    Accepted Manuscript Full Text Available