Convergence Analysis of Alternating Direction Method of Multipliers for Convex Optimization
- 주제(키워드) Convex Optimization , Alternating Direction Method of Multipliers , Dual problem , Saddle point , Separating Hyperplane Theorem
- 발행기관 서강대학교 일반대학원
- 지도교수 김현석
- 발행년도 2020
- 학위수여년월 2020. 2
- 학위명 석사
- 학과 및 전공 일반대학원 수학과
- UCI I804:11029-000000064842
- 본문언어 영어
- 저작권 서강대학교 논문은 저작권보호를 받습니다.
초록/요약
There are many algorithms to solve problems with a large data set. The larger the size of the data, the longer computational time to run. Also, it is hard to find whether a problem is well-posed if its algorithm is not guaranteed to terminate in finite time. Hence it is natural to study the convergence of algorithm. In this thesis, we prove the convergence of Alternating Direction Method of Multipliers (ADMM) under general assumptions. Finally, we attach the numerical experiments for ADMM, which work well.
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