22 citations · 65 across the 18 of their papers we have counts for
19 papers
An Event-Driven Framework for Fly-Inspired Visual Motion Detection
Qinbing Fu, Jingyu Huang, Yan Xie +2
Fast and reliable motion detection is essential for machine vision and autonomous systems operating in dynamic environments. This work integrates emerging event-based sensing with…
Four-operator splitting algorithms for solving monotone inclusions
Jinjian Chen, Yuchao Tang
Monotone inclusions involving the sum of three maximally monotone operators or more have received much attention in recent years. In this paper, we propose three splitting algorith…
Forward-partial inverse-half-forward splitting algorithm for solving monotone inclusions
Luis M. Briceño-Arias, Jinjian Chen, Fernando Roldán +1
In this paper we provide a splitting algorithm for solving coupled monotone inclusions in a real Hilbert space involving the sum of a normal cone to a vector subspace, a maximally…
An outer reflected forward-backward splitting algorithm for solving monotone inclusions
Hui Yu, Chunxiang Zong, Yuchao Tang
Monotone inclusions have wide applications in solving various convex optimization problems arising in signal and image processing, machine learning, and medical image reconstructio…
Convergence analysis of a relaxed inertial alternating minimization algorithm with applications
Yang Yang, Yuchao Tang, Jigen Peng
The alternating direction method of multipliers (ADMM) is a popular method for solving convex separable minimization problems with linear equality constraints. The generalization o…
An inertial alternating direction method of multipliers for solving a two-block separable convex minimization problem
Yang Yang, Yuchao Tang
The alternating direction method of multipliers (ADMM) is a widely used method for solving many convex minimization models arising in signal and image processing. In this paper, we…
Convergence analysis of an inexact inertial Krasnoselskii-Mann algorithm with applications
Fuying Cui, Yang Yang, Yuchao Tang +1
The classical Krasnoselskii-Mann iteration is broadly used for approximating fixed points of nonexpansive operators. To accelerate the convergence of the Krasnoselskii-Mann iterati…
An inertial three-operator splitting algorithm with applications to image inpainting
Fuying Cui, Yuchao Tang, Yang Yang
The three-operators splitting algorithm is a popular operator splitting method for finding the zeros of the sum of three maximally monotone operators, with one of which is cocoerci…
Convergence analysis of a variable metric forward-backward splitting algorithm with applications
Fuying Cui, Yuchao Tang, Chuanxi Zhu
The forward-backward splitting algorithm is a popular operator-splitting method for solving monotone inclusion of the sum of a maximal monotone operator and a cocoercive operator.…
Bounded perturbation resilience of extragradient-type methods and their applications
Qiao-Li Dong, Aviv Gibali, Dan Jiang +1
In this paper we study the bounded perturbation resilience of the extragradient and the subgradient extragradient methods for solving variational inequality (VI) problem in real Hi…
A first-order splitting method for solving a large-scale composite convex optimization problem
Yu-Chao Tang, Guo-Rong Wu, Chuan-Xi Zhu
The forward-backward operator splitting algorithm is one of the most important methods for solving the optimization problem of the sum of two convex functions, where one is differe…
A general framework for solving convex optimization problems involving the sum of three convex functions
Yu-Chao Tang, Guo-Rong Wu, Chuan-Xi Zhu
In this paper, we consider solving a class of convex optimization problem which minimizes the sum of three convex functions , where is differentiable with a…
An inertial primal-dual fixed point algorithm for composite optimization problems
Meng Wen, Yu-Chao Tang, Jigen Peng
We consider an inertial primal-dual fixed point algorithm (IPDFP) to compute the minimizations of the following Problem (1.1). This is a full splitting approach, in the sense that…
Efficient primal-dual fixed point algorithm with dynamic stepsize for convex problems with applications to imaging restoration
Meng Wen, Shigang Yue, Yuchao Tang +1
We consider the problem of finding the minimization of the sum of a convex function and the composition of another convex function with a continuous linear operator from the view o…
A stochastic coordinate descent inertial primal-dual algorithm for large-scale composite optimization
Meng Wen, Yu-Chao Tang, Jigen Peng
We consider an inertial primal-dual algorithm to compute the minimizations of the sum of two convex functions and the composition of another convex function with a continuous linea…
A stochastic coordinate descent splitting primal-dual fixed point algorithm and applications to large-scale composite optimization
Meng Wen, Yu-Chao Tang, Jigen Peng
We consider the problem of finding the minimizations of the sum of two convex functions and the composition of another convex function with a continuous linear operator from the vi…
A stochastic coordinate descent primal-dual algorithm with dynamic stepsize for large-scale composite optimization
Meng Wen, Shigang Yue, Yuchao Tang +1
In this paper we consider the problem of finding the minimizations of the sum of two convex functions and the composition of another convex function with a continuous linear operat…
A splitting primal-dual proximity algorithm for solving composite optimization problems
Yu-Chao Tang, Chuan-Xi Zhu, Meng Wen +1
Our work considers the optimization of the sum of a non-smooth convex function and a finite family of composite convex functions, each one of which is composed of a convex function…
A Warm Restart Strategy for Solving Sudoku by Sparse Optimization Methods
Yuchao Tang, Zhenggang Wu, Chuanxi Zhu
This paper is concerned with the popular Sudoku problem. We proposed a warm restart strategy for solving Sudoku puzzles, based on the sparse optimization technique. Furthermore, we…