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On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging


Jun 30, 2021
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan


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ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction


Jun 10, 2021
Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma

* This paper integrates previous two manuscripts: arXiv:2006.08558 and arXiv:2010.14765, with significantly improved organization, presentation, and new results; V2 polishes writing and adds citation 

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Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization


Apr 27, 2021
Yaodong Yu, Tianyi Lin, Eric Mazumdar, Michael I. Jordan

* The first three authors contributed equally to this work; 37 pages, 20 figures 

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Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition


Mar 17, 2021
Yaodong Yu, Zitong Yang, Edgar Dobriban, Jacob Steinhardt, Yi Ma


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Deep Networks from the Principle of Rate Reduction


Oct 27, 2020
Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma


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Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients


Sep 28, 2020
Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan Yao

* 16 pages 

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Boundary thickness and robustness in learning models


Jul 09, 2020
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney


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Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction


Jun 15, 2020
Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma


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Rethinking Bias-Variance Trade-off for Generalization of Neural Networks


Mar 21, 2020
Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma


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Theoretically Principled Trade-off between Robustness and Accuracy


Jan 24, 2019
Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan

* Technical details of the winning entry to the NeurIPS 2018 Adversarial Vision Challenge 

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Learning One-hidden-layer ReLU Networks via Gradient Descent


Jun 20, 2018
Xiao Zhang, Yaodong Yu, Lingxiao Wang, Quanquan Gu

* 26 pages, 2 figures 

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Third-order Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima


Dec 18, 2017
Yaodong Yu, Pan Xu, Quanquan Gu

* 25 pages 

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Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently


Dec 11, 2017
Yaodong Yu, Difan Zou, Quanquan Gu

* 31 pages, 1 table 

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