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Kronecker-factored Quasi-Newton Methods for Convolutional Neural Networks

Feb 12, 2021
Yi Ren, Donald Goldfarb

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Practical Quasi-Newton Methods for Training Deep Neural Networks

Jun 16, 2020
Donald Goldfarb, Yi Ren, Achraf Bahamou

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A Dynamic Sampling Adaptive-SGD Method for Machine Learning

Dec 31, 2019
Achraf Bahamou, Donald Goldfarb

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Efficient Subsampled Gauss-Newton and Natural Gradient Methods for Training Neural Networks

Jun 05, 2019
Yi Ren, Donald Goldfarb

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Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models

May 24, 2019
Yunfei Teng, Wenbo Gao, Francois Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller

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Scalable Robust Matrix Recovery: Frank-Wolfe Meets Proximal Methods

May 29, 2017
Cun Mu, Yuqian Zhang, John Wright, Donald Goldfarb

* SIAM Journal on Scientific Computing, 2016, Vol. 38, No. 5 : pp. A3291-A3317 

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Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization

May 21, 2017
Xiao Wang, Shiqian Ma, Donald Goldfarb, Wei Liu

* published in SIAM Journal on Optimization 

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Robust Low-rank Tensor Recovery: Models and Algorithms

Nov 24, 2013
Donald Goldfarb, Zhiwei Qin

* appearing in SIAM Journal on Matrix Analysis and Applications 

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Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery

Aug 15, 2013
Cun Mu, Bo Huang, John Wright, Donald Goldfarb

* Slight modifications are made in this second version (mainly, Lemma 5) 

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Structured Sparsity via Alternating Direction Methods

Dec 15, 2011
Zhiwei Qin, Donald Goldfarb

* Journal of Machine Learning Research 13 (2012) 1435-1468 

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Sparse Inverse Covariance Selection via Alternating Linearization Methods

Oct 30, 2010
Katya Scheinberg, Shiqian Ma, Donald Goldfarb

* NIPS 2010 

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Fast Alternating Linearization Methods for Minimizing the Sum of Two Convex Functions

Oct 13, 2010
Donald Goldfarb, Shiqian Ma, Katya Scheinberg

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