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Quanquan Gu

Structure-informed Language Models Are Protein Designers

Feb 09, 2023
Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei YE, Quanquan Gu

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* 10 pages; ver.2 update: added image credit to RFdiffusion (Watson et al., 2022) in Fig. 1F, and fixed some small presentation errors

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Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes

Dec 12, 2022
Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu

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* 44 pages, 1 table

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Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes

Dec 12, 2022
Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang

* We study the corruption-robust MDPs and contextual bandits with general function approximation

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Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium

Aug 10, 2022
Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan

* 42 pages

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Towards Understanding Mixture of Experts in Deep Learning

Aug 04, 2022
Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li

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* 53 pages, 8 figures, 11 tables

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The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift

Aug 03, 2022
Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

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* 32 pages, 1 figure, 1 table

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

Jul 07, 2022
Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu

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* 25 pages, 1 figure, 2 tables

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