Convergence rate analysis of proximal gradient methods with applications to composite minimization problems-Reference-Cited by-同舟云学术

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Convergence rate analysis of proximal gradient methods with applications to composite minimization problems

Published:2020-01-22 Issue:1 Volume:70 Page:75-100
ISSN:0233-1934
Container-title:Optimization
language:en
Short-container-title:Optimization

Author:

Sahu D. R.¹,Yao J. C.²,Verma M.³,Shukla K. K.⁴

Affiliation:

1. Department of Mathematics, Banaras Hindu University, Varanasi, India

2. Research Center for Interneural Computing, China Medical University Hospital, China Medical University, Taichung, Taiwan

3. Institute for Research and Development in Banking Technology, Hyderabad, India

4. Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, India

Funder

MOST

Publisher

Informa UK Limited

Subject

Applied Mathematics,Management Science and Operations Research,Control and Optimization

Link

https://www.tandfonline.com/doi/pdf/10.1080/02331934.2019.1702040

Reference40 articles.

1. Convex Analysis and Monotone Operator Theory in Hilbert Spaces

2. Signal Recovery by Proximal Forward-Backward Splitting

3. Face recognition by sparse discriminant analysis via joint L2,1-norm minimization

4. A Modified Forward-Backward Splitting Method for Maximal Monotone Mappings

5. Smoothing algorithms for computing the projection onto a Minkowski sum of convex sets

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