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math.OC2024
ripALM: A Relative-Type Inexact Proximal Augmented Lagrangian Method for Linearly Constrained Convex Optimization
Jiayi Zhu, Ling Liang, Lei Yang +1
Inexact proximal augmented Lagrangian methods (ipALMs) have been widely used for solving linearly constrained convex optimization problems, owing to their strong theoretical guaran…
math.OC2024
An Inexact Bregman Proximal Difference-of-Convex Algorithm with Two Types of Relative Stopping Criteria
Lei Yang, Jingjing Hu, Kim-Chuan Toh
In this paper, we consider a class of difference-of-convex (DC) optimization problems, which require only a weaker restricted -smooth adaptable property on the smooth part of th…