most citedRandomized double and triple Kaczmarz for solving extended normal equations

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math.NA2020

Pseudoinverse-free randomized block iterative algorithms for consistent and inconsistent linear systems

Kui Du, Xiao-Hui Sun

Randomized iterative algorithms have attracted much attention in recent years because they can approximately solve large-scale linear systems of equations without accessing the ent…

math.NA20201 cited

Randomized double and triple Kaczmarz for solving extended normal equations

Kui Du, Xiao-Hui Sun

The randomized Kaczmarz algorithm has received considerable attention recently because of its simplicity, speed, and the ability to approximately solve large-scale linear systems o…

math.NA2020

Stochastic gradient descent for linear least squares problems with partially observed data

Kui Du, Xiao-Hui Sun

We propose a novel stochastic gradient descent method for solving linear least squares problems with partially observed data. Our method uses submatrices indexed by a randomly sele…

math.NA2020

Randomized extended block Kaczmarz for solving least squares

Kui Du, Wutao Si, Xiaohui Sun

Randomized iterative algorithms have recently been proposed to solve large-scale linear systems. In this paper, we present a simple randomized extended block Kaczmarz algorithm tha…

math.NA2019

A doubly stochastic block Gauss-Seidel algorithm for solving linear equations

Kui Du, Xiaohui Sun

We propose a simple doubly stochastic block Gauss--Seidel algorithm for solving linear systems of equations. By varying the row partition parameter and the column partition paramet…