Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints-Reference-Cited by-同舟云学术

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Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints

Published:2023-02 Issue:1 Volume:49 Page:
ISSN:1019-7168
Container-title:Advances in Computational Mathematics
language:en
Short-container-title:Adv Comput Math

Author:

Zhang Yongle,Li Guoyin,Pong Ting Kei,Xu Shiqi

Funder

national natural science foundation of china

sichuan science and technology program

australian research council

hong kong research grants council

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Mathematics

Link

https://link.springer.com/content/pdf/10.1007/s10444-022-10002-2.pdf

Reference52 articles.

1. van Ackooij, W., de Oliveira, W.: Convexity and optimization with copulae structured probability constraints. Optimization 65, 1349–1376 (2016)

2. van Ackooij, W., Demassey, S., Javal, P., Morais, H., de Oliveira, W., Swaminathan, B.: A bundle method for nonsmooth DC programming with application to chance-constrained problems. Comput. Optim. Appl. 78, 451–490 (2021)

3. Ahn, M., Pang, J.S., Xin, J.: Difference-of-convex learning: directional stationarity, optimality, and sparsity. SIAM J. Optim. 27, 1637–1665 (2017)

4. Attouch, H., Bolte, J.: On the convergence of the proximal algorithm for nonsmooth functions involving analytic features. Math. Program. 116, 5–16 (2009)

5. Attouch, H., Bolte, J., Redont, P., Soubeyran, A.: Proximal alternating minimization and projection methods for nonconvex problems: an approach based on the kurdyka-Łojasiewicz inequality. Math. Oper. Res. 35, 438–457 (2010)

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