activity
20222024
most citedOn the convergence analysis of the greedy randomized Kaczmarz method

2 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

math.NA2024★ 1 cited

On adaptive stochastic extended iterative methods for solving least squares

Yun Zeng, Deren Han, Yansheng Su +1

In this paper, we propose a novel adaptive stochastic extended iterative method, which can be viewed as an improved extension of the randomized extended Kaczmarz (REK) method, for…

math.NA2023

On greedy multi-step inertial randomized Kaczmarz method for solving linear systems

Yansheng Su, Deren Han, Yun Zeng +1

The multi-step inertial randomized Kaczmarz (MIRK) method is an iterative method for solving large-scale linear systems. In this paper, we enhance the MIRK method by incorporating…

math.NA2023★ 2 cited

Stochastic dual coordinate descent with adaptive heavy ball momentum for linearly constrained convex optimization

Yun Zeng, Deren Han, Yansheng Su +1

The problem of finding a solution to the linear system with certain minimization properties arises in numerous scientific and engineering areas. In the era of big data, th…

math.NA2023★ 2 cited

On the convergence analysis of the greedy randomized Kaczmarz method

Yansheng Su, Deren Han, Yun Zeng +1

In this paper, we analyze the greedy randomized Kaczmarz (GRK) method proposed in Bai and Wu (SIAM J. Sci. Comput., 40(1):A592--A606, 2018) for solving linear systems. We develop m…

math.OC2023

On adaptive stochastic heavy ball momentum for solving linear systems

Yun Zeng, Deren Han, Yansheng Su +1

The stochastic heavy ball momentum (SHBM) method has gained considerable popularity as a scalable approach for solving large-scale optimization problems. However, one limitation of…

math.NA2023

Randomized Kaczmarz method with adaptive stepsizes for inconsistent linear systems

Yun Zeng, Deren Han, Yansheng Su +1

We investigate the randomized Kaczmarz method that adaptively updates the stepsize using readily available information for solving inconsistent linear systems. A novel geometric in…

math.OC2022★ 1 cited

Randomized Douglas-Rachford methods for linear systems: Improved accuracy and efficiency

Deren Han, Yansheng Su, Jiaxin Xie

The Douglas-Rachford (DR) method is a widely used method for finding a point in the intersection of two closed convex sets (feasibility problem). However, the method converges weak…