Proximal gradient (forward backward splitting) methods for learning is an area of research in optimization and statistical learning theory whichâ€¦Â (More)

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2016

2016

- Shiqian Ma
- J. Sci. Comput.
- 2016

In this paper, we propose an alternating proximal gradient method that solves convex minimization problems with three or moreâ€¦Â (More)

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2015

2015

- Huan Li, Zhouchen Lin
- NIPS
- 2015

Nonconvex and nonsmooth problems have recently received considerable attention in signal/image processing, statistics and machineâ€¦Â (More)

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2013

2013

We analyze distributed optimization algorithms where parts of data and variables are distributed over several machines andâ€¦Â (More)

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Highly Cited

2012

Highly Cited

2012

- Chenglong Bao, Yi Wu, Haibin Ling, Hui Ji
- 2012 IEEE Conference on Computer Vision andâ€¦
- 2012

Recently sparse representation has been applied to visual tracker by modeling the target appearance using a sparse approximationâ€¦Â (More)

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2012

2012

- Annie I. Chen, Asuman E. Ozdaglar
- 2012 50th Annual Allerton Conference onâ€¦
- 2012

We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the privateâ€¦Â (More)

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Highly Cited

2011

Highly Cited

2011

- Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
- UAI
- 2011

We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty thatâ€¦Â (More)

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Highly Cited

2011

Highly Cited

2011

- Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach
- NIPS
- 2011

We consider the problem of optimizing the sum of a smooth convex function and a non-smooth convex function using proximalâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

We study the problem of estimating high dimensional regression models regularized by a structured-sparsity-inducing penalty thatâ€¦Â (More)

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Highly Cited

2009

Highly Cited

2009

- Zhouchen Lin, Minming Chen, Yi Ma
- ArXiv
- 2009

This paper proposes scalable and fast algorithms for solving the Robust PCA problem, namely recovering a low-rank matrix with anâ€¦Â (More)

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Highly Cited

2009

Highly Cited

2009

The affine rank minimization problem, which consists of finding a matrix of minimum rank subject to linear equality constraintsâ€¦Â (More)

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