Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization
نویسندگان
چکیده
منابع مشابه
Infeasibility detection in the alternating direction method of multipliers for convex optimization
The alternating direction method of multipliers (ADMM) is a powerful operator splitting technique for solving structured optimization problems. For convex optimization problems, it is well-known that the iterates generated by ADMM converge to a solution provided that it exists. If a solution does not exist, then the ADMM iterates do not converge. Nevertheless, we show that the ADMM iterates yie...
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Abstract. Inexact alternating direction multiplier methods (ADMMs) are developed for solving general separable convex optimization problems with a linear constraint and with an objective that is the sum of smooth and nonsmooth terms. The approach involves linearized subproblems, a back substitution step, and either gradient or accelerated gradient techniques. Global convergence is established. ...
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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 it...
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ژورنال
عنوان ژورنال: Journal of Optimization Theory and Applications
سال: 2019
ISSN: 0022-3239,1573-2878
DOI: 10.1007/s10957-019-01575-y