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Borda Regret Minimization for Generalized Linear Dueling Bandits


Mar 15, 2023
Yue Wu, Tao Jin, Hao Lou, Farzad Farnoud, Quanquan Gu

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* 28 pages, 3 figure 

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The Benefits of Mixup for Feature Learning


Mar 15, 2023
Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu

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* 72 pages, 4 figures 

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Benign Overfitting for Two-layer ReLU Networks


Mar 07, 2023
Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu

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* 54 pages, 2 figures, 2 tables 

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Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples


Mar 03, 2023
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade

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* 41 pages, 4 figures 

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Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency


Feb 21, 2023
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

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* 43 pages, 2 tables 

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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

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

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A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning


Sep 30, 2022
Zixiang Chen, Chris Junchi Li, Angela Yuan, Quanquan Gu, Michael I. Jordan

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