In this work, we propose a new method to enhance the convergence rate of an iterative algorithm used to solve a system of equations with an arbitrary condition number. At each stage, the algorithm ...

The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical ...

Asynchronous iterative algorithms have emerged as a robust alternative to traditional synchronous methods for solving large-scale linear systems. These approaches allow individual computational ...

Asynchronous iterative algorithms have emerged as a robust alternative to traditional synchronous methods for solving large-scale linear systems.

We present two first-order primal-dual algorithms for solving saddle point formulations of linear programs, namely FWLP (Frank-Wolfe Linear Programming) and FWLP-P. The former iteratively applies the ...

We propose and study a new iterative coordinate descent algorithm (QICD) for solving nonconvex penalized quantile regression in high dimension. By permitting different subsets of covariates to be ...

We present an O (√n L)-iteration homogeneous and self-dual linear programming (LP) algorithm. The algorithm possesses the following features: • It solves the linear programming problem without any ...