%0 Journal Article
%T 正则化Consensus问题的收敛性证明<br>Convergence Proof of Regularized Consensus Problems
%A 刘玉洁
%A 毕文静
%A 张炎
%A 俞露
%A 李伟南
%J Pure Mathematics
%P 371-376
%@ 2160-7605
%D 2021
%I Hans Publishing
%R 10.12677/PM.2021.113049
%X <div style=\"text-align:justify;\">
	交替方向乘子法(ADMM算法)是求解可分离凸优化问题的一种有效方法。该算法利用目标函数的可分性，将原问题拆分成若干个极小化的子问题，然后交替迭代求解。而一致性(Consensus)问题是求解大数据问题的重要的一种形式，本文提出了一种正则化的一致性问题，给出了其迭代过程，并在适当的假设下，证明了其收敛性。<br />
Alternating direction multiplier method (ADMM algorithm) is an effective method to solve sepa-rable convex optimization problems. The algorithm USES the separability of the objective function to divide the original problem into several minimization subproblems and then solve them alter-nately iteratively. Consensus is an important form of solving big data problems. In this paper, a regularized consistency problem is proposed, its iterative process is given, and its convergence is proved under appropriate assumptions.
</div>
%K ADMM，Consensus，收敛性<br>ADMM
%K Consensus
%K The Convergence
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=41368