2 citations · 5 across the 7 of their papers we have counts for
7 papers
Randomized conjugate gradient least squares
Yun Zeng, Jian-Feng Cai, Deren Han +1
We develop a novel randomized conjugate gradient least squares (RCGLS) method for solving least-squares problems, in which iterative sketching is employed at each step to reduce th…
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…
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…
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…
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…
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…
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…