11 papers
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…
A Hybrid Subgradient Method for Nonsmooth Nonconvex Bilevel Optimization
Nachuan Xiao, Xiaoyin Hu, Xin Liu +1
In this paper, we focus on the nonconvex-nonconvex bilevel optimization problem (BLO), where both upper-level and lower-level objectives are nonconvex, with the upper-level problem…
Convergence Analysis of a Relative-type Inexact Preconditioned Proximal ALM for Convex Nonlinear Programming
Lei Yang, Jiayi Zhu, Ling Liang +1
This article investigates the convergence properties of a relative-type inexact preconditioned proximal augmented Lagrangian method (ripALM) for convex nonlinear programming, a…
Robust principal component analysis with rank and cardinality regularization under matrix factorization
Wenjing Li, Wei Bian, Kim-Chuan Toh
Robust principal component analysis is an important representative method in data analysis. It is usually viewed as an optimization problem involving the rank and -norm of…
On the efficient computation of proximal operators of affine-constrained nonconvex functions
Di Hou, Tianyun Tang, Kim-Chuan Toh +1
Proximal operators with affine constraints arise in numerous models in nonconvex projection, composite optimization, and structured regularization. However, their efficient computa…
Partial Envelope for Optimization Problem with Nonconvex Constraints
Xiaoyin Hu, Xin Liu, Kim-Chuan Toh +1
In this paper, we consider the nonlinear constrained optimization problem (NCP) with constraint set , where is a closed convex subset…