activity
20202022
most citedGreedy Block Gauss-Seidel Methods for Solving Large Linear Least Squares Problem

6 citations · 18 across the 17 of their papers we have counts for

collaborators

19 papers

math.NA20221 cited

Subsampling for tensor least squares: Optimization and statistical perspectives

Ling Tang, Hanyu Li

In this paper, we investigate the random subsampling method for tensor least squares problem with respect to the popular t-product. From the optimization perspective, we present th…

math.NA2022

Randomized block subsampling Kaczmarz-Motzkin method

Yanjun Zhang, Hanyu Li

By introducing a subsampling strategy, we propose a randomized block Kaczmarz-Motzkin method for solving linear systems. Such strategy not only determines the block size, but also…

math.NA2022

Practical Alternating Least Squares for Tensor Ring Decomposition

Yajie Yu, Hanyu Li

Tensor ring (TR) decomposition has been widely applied as an effective approach in a variety of applications to discover the hidden low-rank patterns in multidimensional data. A we…

math.NA20221 cited

On sketch-and-project methods for solving tensor equations

Ling Tang, Yanjun Zhang, Hanyu Li

We first propose the regular sketch-and-project method for solving tensor equations with respect to the popular t-product. Then, three adaptive sampling strategies and three corres…

math.NA20222 cited

Greedy capped nonlinear Kaczmarz methods

Yanjun Zhang, Hanyu Li

To solve nonlinear problems, we construct two kinds of greedy capped nonlinear Kaczmarz methods by setting a capped threshold and introducing an effective probability criterion for…

math.NA20222 cited

Greedy randomized sampling nonlinear Kaczmarz methods

Yanjun Zhang, Hanyu Li, Ling Tang

The nonlinear Kaczmarz method was recently proposed to solve the system of nonlinear equations. In this paper, we first discuss two greedy selection rules, i.e., the maximum residu…