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• W2953057288 abstract "The mirror descent algorithm (MDA) generalizes gradient descent by using a Bregman divergence to replace squared Euclidean distance. In this paper, we similarly generalize the alternating direction method of multipliers (ADMM) to Bregman ADMM (BADMM), which allows the choice of different Bregman divergences to exploit the structure of problems. BADMM provides a unified framework for ADMM and its variants, including generalized ADMM, inexact ADMM and Bethe ADMM. We establish the global convergence and the $O(1/T)$ iteration complexity for BADMM. In some cases, BADMM can be faster than ADMM by a factor of $O(n/log(n))$. In solving the linear program of mass transportation problem, BADMM leads to massive parallelism and can easily run on GPU. BADMM is several times faster than highly optimized commercial software Gurobi." @default.
• W2953057288 created "2019-06-27" @default.
• W2953057288 creator A5014459472 @default.
• W2953057288 creator A5064096962 @default.
• W2953057288 date "2013-06-13" @default.
• W2953057288 modified "2023-09-27" @default.
• W2953057288 title "Bregman Alternating Direction Method of Multipliers" @default.
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• W2953057288 hasPublicationYear "2013" @default.
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