7 papers
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…
Inexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization
Yang Yang, Marius Pesavento, Zhi-Quan Luo +1
In this paper, we propose an inexact block coordinate descent algorithm for large-scale nonsmooth nonconvex optimization problems. At each iteration, a particular block variable is…
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…
Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations
Yang Yang, Marius Pesavento, Symeon Chatzinotas +1
In this paper, we propose a successive convex approximation framework for sparse optimization where the nonsmooth regularization function in the objective function is nonconvex and…
A Parallel Best-Response Algorithm with Exact Line Search for Nonconvex Sparsity-Regularized Rank Minimization
Yang Yang, Marius Pesavento
In this paper, we propose a convergent parallel best-response algorithm with the exact line search for the nondifferentiable nonconvex sparsity-regularized rank minimization proble…