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Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise

Aug 04, 2020
Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang

* 31 pages, 4 figures 

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Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary

Jul 21, 2020
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu


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Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia

Jul 17, 2020
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama

* 25 pages, 8 figures 

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On Layer Normalization in the Transformer Architecture

Feb 12, 2020
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu


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Gradient Perturbation is Underrated for Differentially Private Convex Optimization

Nov 26, 2019
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin


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Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data

May 29, 2019
Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu


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Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network

Mar 17, 2019
Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu

* 33 pages, 5 figures 

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SGD Converges to Global Minimum in Deep Learning via Star-convex Path

Jan 02, 2019
Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh

* ICLR2019 

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$\mathcal{G}$-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space

Oct 09, 2018
Qi Meng, Wei Chen, Shuxin Zheng, Huishuai Zhang, Qiwei Ye, Zhi-Ming Ma, Tie-Yan Liu


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Capacity Control of ReLU Neural Networks by Basis-path Norm

Sep 19, 2018
Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu


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Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation

Feb 27, 2018
Huishuai Zhang, Wei Chen, Tie-Yan Liu

* 12 pages, 3 figures 

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Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization

Feb 19, 2018
Yi Zhou, Yingbin Liang, Huishuai Zhang


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Block-diagonal Hessian-free Optimization for Training Neural Networks

Dec 20, 2017
Huishuai Zhang, Caiming Xiong, James Bradbury, Richard Socher

* 10 pages, 3 figures 

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Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent

Sep 23, 2017
Yuanxin Li, Yuejie Chi, Huishuai Zhang, Yingbin Liang

* 30 pages, 3 figures 

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Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers

May 18, 2017
Huishuai Zhang, Yuejie Chi, Yingbin Liang

* journal version under review 

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Reshaped Wirtinger Flow and Incremental Algorithm for Solving Quadratic System of Equations

Oct 27, 2016
Huishuai Zhang, Yi Zhou, Yingbin Liang, Yuejie Chi

* Part of this draft is accepted to NIPS 2016 

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