Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming
Author:
Affiliation:
1. Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, MN 55455 USA.
2. Huawei Technologies Canada, Burnaby V5C 6S7, BC, Canada.
Funder
NSF
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Subject
Theoretical Computer Science,Software,Applied Mathematics
Reference27 articles.
1. A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization
2. An Augmented Lagrangian Method for Total Variation Video Restoration
3. First-order methods of smooth convex optimization with inexact oracle
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Accelerated First-Order Methods for Convex Optimization with Locally Lipschitz Continuous Gradient;SIAM Journal on Optimization;2023-08-30
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