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20152023
most citedAn inexact Douglas-Rachford splitting method for solving absolute value equations

33 citations · 103 across the 18 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

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.OC2023

Improving the generalization via coupled tensor norm regularization

Ying Gao, Yunfei Qu, Chunfeng Cui +1

In this paper, we propose a coupled tensor norm regularization that could enable the model output feature and the data input to lie in a low-dimensional manifold, which helps us to…

math.OC2023

Understanding the convergence of the preconditioned PDHG method: a view of indefinite proximal ADMM

Yumin Ma, Xingju Cai, Bo Jiang +1

The primal-dual hybrid gradient (PDHG) algorithm is popular in solving min-max problems which are being widely used in a variety of areas. To improve the applicability and efficien…

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…