Convergence of Min-Sum Message-Passing for Convex Optimization

被引:30
作者
Moallemi, Ciamac C. [1 ]
Van Roy, Benjamin [2 ,3 ]
机构
[1] Columbia Univ, Grad Sch Business, New York, NY 10027 USA
[2] Stanford Univ, Dept Management Sci & Engn, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
基金
美国国家科学基金会;
关键词
Message-passing algorithms; decentralized optimization; convex optimization; BELIEF PROPAGATION; CORRECTNESS; PRODUCT;
D O I
10.1109/TIT.2010.2040863
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We establish that the min-sum message-passing algorithm and its asynchronous variants converge for a large class of unconstrained convex optimization problems, generalizing existing results for pairwise quadratic optimization problems. The main sufficient condition is that of scaled diagonal dominance. This condition is similar to known sufficient conditions for asynchronous convergence of other decentralized optimization algorithms, such as coordinate descent and gradient descent.
引用
收藏
页码:2041 / 2050
页数:10
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