Accelerated dual-averaging primal–dual method for composite convex minimization-Reference-Cited by-同舟云学术

Accelerated dual-averaging primal–dual method for composite convex minimization

Published:2020-01-20 Issue:4 Volume:35 Page:741-766
ISSN:1055-6788
Container-title:Optimization Methods and Software
language:en
Short-container-title:Optimization Methods and Software

Author:

Tan Conghui¹,Qian Yuqiu²,Ma Shiqian³,Zhang Tong⁴

Affiliation:

1. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, People's Republic of China

2. Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, People's Republic of China

3. Department of Mathematics, University of California, Davis, CA, USA

4. Departments of Computer Science and Mathematics, The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, People's Republic of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Control and Optimization,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/10556788.2020.1713779

Reference27 articles.

1. Z. Allen-Zhu, Katyusha: The first direct acceleration of stochastic gradient methods, in Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing. ACM, 2017, pp. 1200–1205.

2. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

3. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging

4. A. Defazio, F. Bach, and S. Lacoste-Julien, SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives, in Advances in neural information processing systems. 2014, pp. 1646–1654.

5. Learning in high-dimensional multimedia data: the state of the art

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