2 citations · 4 across the 9 of their papers we have counts for
9 papers
Randomized iterative methods with Polyak step-size for solving generalized absolute value equations
Jiayun Chen, Qiye Zhang, Deren Han +1
In this paper, we systematically incorporate the Polyak step-size into the randomized iterative method to improve its efficiency for solving generalized absolute value equations. I…
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…
Enhanced randomized Douglas-Rachford method for linear systems: Improved probabilities and adaptive momentum
Liqi Guo, Ruike Xiang, Deren Han +1
Randomized iterative methods have gained recent interest in machine learning and signal processing for solving large-scale linear systems. One such example is the randomized Dougla…
Connecting randomized iterative methods with Krylov subspaces
Yonghan Sun, Deren Han, Jiaxin Xie
Randomized iterative methods, such as the randomized Kaczmarz method, have gained significant attention for solving large-scale linear systems due to their simplicity and efficienc…
A distributed Douglas-Rachford splitting method for solving linear constrained multi-block weakly convex problems
Leyu Hu, Jiaxin Xie, Xingju Cai +1
In recent years, a distributed Douglas-Rachford splitting method (DDRSM) has been proposed to tackle multi-block separable convex optimization problems. This algorithm offers relat…
A simple linear convergence analysis of the randomized reshuffling Kaczmarz method
Deren Han, Jiaxin Xie
The random reshuffling Kaczmarz (RRK) method enjoys the simplicity and efficiency in solving linear systems as a Kaczmarz-type method, whereas it also inherits the practical improv…
Novel clustered federated learning based on local loss
Endong Gu, Yongxin Chen, Hao Wen +2
This paper proposes LCFL, a novel clustering metric for evaluating clients' data distributions in federated learning. LCFL aligns with federated learning requirements, accurately a…
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…
Randomized iterative methods for generalized absolute value equations: Solvability and error bounds
Jiaxin Xie, Hou-Duo Qi, Deren Han
Randomized iterative methods, such as the Kaczmarz method and its variants, have gained growing attention due to their simplicity and efficiency in solving large-scale linear syste…