Smooth strongly convex interpolation and exact worst-case performance of first-order methods-Reference-Cited by-同舟云学术

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Smooth strongly convex interpolation and exact worst-case performance of first-order methods

Published:2016-05-17 Issue:1-2 Volume:161 Page:307-345
ISSN:0025-5610
Container-title:Mathematical Programming
language:en
Short-container-title:Math. Program.

Author:

Taylor Adrien B.,Hendrickx Julien M.,Glineur François

Funder

Wallonia-Brussels Federation - Concerted Research Actions

Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture

Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Software

Link

http://link.springer.com/content/pdf/10.1007/s10107-016-1009-3.pdf

Reference26 articles.

1. Bauschke, H., Combettes, P.: Convex analysis and monotone operator theory in Hilbert spaces. Springer, Berlin (2011)

2. Beck, A.: Quadratic matrix programming. SIAM J. Optim. 17(4), 1224–1238 (2007)

3. Beck, A., Teboulle, M.: Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. Image Process. IEEE Trans. 18(11), 2419–2434 (2009)

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

5. Ben-Tal, A., Nemirovski, A.: Lectures on modern convex optimization: analysis, algorithms, and engineering applications, vol. 2. SIAM, Philadelphia (2001)

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