On adaptive stochastic heavy ball momentum for solving linear systems
The stochastic heavy ball momentum (SHBM) method has gained considerable popularity
as a scalable approach for solving large-scale optimization problems. However, one …
as a scalable approach for solving large-scale optimization problems. However, one …
Randomized Douglas–Rachford Methods for Linear Systems: Improved Accuracy and Efficiency
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 …
intersection of two closed convex sets (feasibility problem). However, the method converges …
Randomized iterative methods for generalized absolute value equations: Solvability and error bounds
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 systems …
growing attention due to their simplicity and efficiency in solving large-scale linear systems …
Randomized Kaczmarz method with adaptive stepsizes for inconsistent linear systems
We investigate the randomized Kaczmarz method that adaptively updates the stepsize using
readily available information for solving inconsistent linear systems. A novel geometric …
readily available information for solving inconsistent linear systems. A novel geometric …
Fast stochastic dual coordinate descent algorithms for linearly constrained convex optimization
The problem of finding a solution to the linear system $ Ax= b $ with certain minimization
properties arises in numerous scientific and engineering areas. In the era of big data, the …
properties arises in numerous scientific and engineering areas. In the era of big data, the …
The linear convergence of the greedy randomized Kaczmarz method is deterministic
To improve the convergence property of the randomized Kaczmarz (RK) method for solving
linear systems, Bai and Wu (SIAM J. Sci. Comput., 40 (1): A592--A606, 2018) originally …
linear systems, Bai and Wu (SIAM J. Sci. Comput., 40 (1): A592--A606, 2018) originally …
On the adaptive deterministic block Kaczmarz method with momentum for solving large-scale consistent linear systems
L Tan, X Guo, M Deng, J Chen - Journal of Computational and Applied …, 2025 - Elsevier
The Kaczmarz method is a traditional and widely used iterative algorithm for solving large-
scale consistent linear systems, while its improved block Kaczmarz-type methods have …
scale consistent linear systems, while its improved block Kaczmarz-type methods have …
On adaptive stochastic extended iterative methods for solving least squares
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 …
be viewed as an improved extension of the randomized extended Kaczmarz (REK) method …
A simple linear convergence analysis of the reshuffling Kaczmarz method
The Kaczmarz method and its variants, which are types of stochastic gradient descent (SGD)
methods, have been extensively studied for their simplicity and efficiency in solving linear …
methods, have been extensively studied for their simplicity and efficiency in solving linear …
On the adaptive deterministic block coordinate descent methods with momentum for solving large linear least-squares problems
LZ Tan, MY Deng, JL Qiu, XP Guo - arXiv preprint arXiv:2410.20108, 2024 - arxiv.org
In this work, we first present an adaptive deterministic block coordinate descent method with
momentum (mADBCD) to solve the linear least-squares problem, which is based on …
momentum (mADBCD) to solve the linear least-squares problem, which is based on …