A unified approach to error bounds for structured convex optimization problems-Reference-Cited by-同舟云学术

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A unified approach to error bounds for structured convex optimization problems

Published:2017-01-25 Issue:2 Volume:165 Page:689-728
ISSN:0025-5610
Container-title:Mathematical Programming
language:en
Short-container-title:Math. Program.

Author:

Zhou Zirui,So Anthony Man-Cho

Funder

Hong Kong Research Grants Council General Research Fund Project CUHK

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Software

Link

http://link.springer.com/article/10.1007/s10107-016-1100-9/fulltext.html

Reference47 articles.

1. Argyriou, A., Evgeniou, T., Pontil, M.: Convex multi-task feature learning. Mach. Learn. 73(3), 243–272 (2008)

2. Azé, D., Hiriart-Urruty, J.-B.: Optimal Hoffman-type estimates in eigenvalue and semidefinite inequality constraints. J. Glob. Optim. 24(2), 133–147 (2002)

3. Bauschke, H.H., Borwein, J.M.: On projection algorithms for solving convex feasibility problems. SIAM Rev. 38(3), 367–426 (1996)

4. Bauschke, H.H., Borwein, J.M., Li, W.: Strong conical hull intersection property, bounded linear regularity, Jameson’s property (G), and error bounds in convex optimization. Math. Program. Ser. A 86(1), 135–160 (1999)

5. Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2(1), 183–202 (2009)

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