53 citations · 144 across the 20 of their papers we have counts for
7 papers · 1 filter
Bregman Proximal Gradient Algorithm with Extrapolation for a class of Nonconvex Nonsmooth Minimization Problems
Xiaoya Zhang, Roberto Barrio, M. Angeles Martinez +2
In this paper, we consider an accelerated method for solving nonconvex and nonsmooth minimization problems. We propose a Bregman Proximal Gradient algorithm with extrapolation(BPGe…
Non-ergodic Complexity of Convex Proximal Inertial Gradient Descents
Tao Sun, Linbo Qiao, Dongsheng Li
The proximal inertial gradient descent is efficient for the composite minimization and applicable for broad of machine learning problems. In this paper, we revisit the computationa…
A convergence framework for inexact nonconvex and nonsmooth algorithms and its applications to several iterations
Tao Sun, Hao Jiang, Lizhi Cheng +1
In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error co…
Variants of alternating minimization method with sublinear rates of convergence for convex optimization
Hui Zhang, Lizhi Cheng
The alternating minimization (AM) method is a fundamental method for minimizing convex functions whose variable consists of two blocks. How to efficiently solve each subproblems wh…
Projected shrinkage algorithm for box-constrained L1-minimization
Hui Zhang, Lizhi Cheng
Box-constrained L1-minimization can perform remarkably better than classical L1-minimization when correction box constraints are available. And also many practical L1-minimization…
Proximal linearized iteratively reweighted least squares for a class of nonconvex and nonsmooth problems
Hui Zhang, Tao Sun, Lizhi Cheng
For solving a wide class of nonconvex and nonsmooth problems, we propose a proximal linearized iteratively reweighted least squares (PL-IRLS) algorithm. We first approximate the or…
A dual algorithm for a class of augmented convex models
Hui Zhang, Lizhi Cheng, Wotao Yin
Convex optimization models find interesting applications, especially in signal/image processing and compressive sensing. We study some augmented convex models, which are perturbed…