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The Bregman method is an iterative algorithm to solve certain convex optimization problems involving regularization.[1] The original version is due to Lev M. Bregman, who published it in 1967.[2]
The algorithm is a row-action method accessing constraint functions one by one and the method is particularly suited for large optimization problems where constraints can be efficiently enumerated[citation needed]. The algorithm works particularly well for regularizers such as the norm, where it converges very quickly because of an error-cancellation effect.[3]
- ^ Xiong, Kai; Zhao, Guanghui; Shi, Guangming; Wang, Yingbin (2019-09-12). "A Convex Optimization Algorithm for Compressed Sensing in a Complex Domain: The Complex-Valued Split Bregman Method". Sensors. 19 (20) (published 18 Oct 2019): 4540. Bibcode:2019Senso..19.4540X. doi:10.3390/s19204540. PMC 6832202. PMID 31635423.
- ^ Bregman L. "A Relaxation Method of Finding a Common Point of Convex Sets and its Application to Problems of Optimization". Dokl. Akad. Nauk SSSR, v. 171, No. 5, 1966, p.p. 1019-1022. (English translation: Soviet Math. Dokl., v. 7, 1966, p.p. 1578-1581)
- ^ Yin, Wotao (8 Dec 2009). "The Bregman Methods: Review and New Results" (PDF). Archived (PDF) from the original on 2010-06-13. Retrieved 16 Apr 2021.