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Quanquan Gu

Iterative Teacher-Aware Learning

Oct 01, 2021
Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu

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* Advances in Neural Information Processing Systems (2021)

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Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization

Aug 25, 2021
Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu

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* 42 pages, 2 figures and 1 table

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The Benefits of Implicit Regularization from SGD in Least Squares Problems

Aug 10, 2021
Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham M. Kakade

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* 39 pages, 1 figure

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Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent

Jul 20, 2021
Spencer Frei, Quanquan Gu

* 15 pages

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Self-training Converts Weak Learners to Strong Learners in Mixture Models

Jul 16, 2021
Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu

* 21 pages

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Variance-Aware Off-Policy Evaluation with Linear Function Approximation

Jun 22, 2021
Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu

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* 70 pages, 4 figures

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