Bregman method
Iterative algorithm to solve certain convex optimization problems involving regularization / From Wikipedia, the free encyclopedia
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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]
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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]