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20212026
most citedAdaptively Sketched Bregman Projection Methods for Linear Systems

15 citations · 17 across the 9 of their papers we have counts for

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9 papers

math.NA2026

Relaxed Greedy Randomized Kaczmarz with Signal Averaging for Solving Doubly-Noisy Linear Systems

Lu Zhang, Jinchuan Zeng, Hui Zhang

Large-scale linear systems of the form are often doubly-noisy, in the sense that both its measurement matrix and measurement vector are noisy. In this paper, we exte…

math.OC2026

Stochastic Block Bregman Projection with Polyak-like Stepsize for Possibly Inconsistent Convex Feasibility Problems

Lu Zhang, Hongzhen Chen, Hongxia Wang +1

Stochastic projection algorithms for solving convex feasibility problems (CFPs) have attracted considerable attention due to their broad applicability. In this paper, we propose a…

math.OC2026

Adaptive Momentum via Minimal Dual Function for Accelerating Randomized Sparse Kaczmarz

Lu Zhang, Jinchuan Zeng, Hongxia Wang +1

Recently, the randomized sparse Kaczmarz method has been accelerated by designing heavy ball momentum adaptively via a minimal-error principle. In this paper, we develop a new adap…

math.OC2024

Nonlinear preconditioned primal-dual method for a class of structured minimax problems

Lu Zhang, Hongxia Wang, Hui Zhang

We propose and analyze a general framework called nonlinear preconditioned primal-dual with projection for solving nonconvex-nonconcave and non-smooth saddle-point problems. The fr…

math.NA2023★ 2 cited

A Weighted Randomized Sparse Kaczmarz Method for Solving Linear Systems

Lu Zhang, Ziyang Yuan, Hongxia Wang +1

The randomized sparse Kaczmarz method, designed for seeking the sparse solutions of the linear systems , selects the -th projection hyperplane with likelihood proportional…

math.OC2022

Quantile-based Random Sparse Kaczmarz for Corrupted and Noisy Linear Systems

Lu Zhang, Hongxia Wang, Hui Zhang

The randomzied Kaczmarz method, along with its recently developed variants, has become a popular tool for dealing with large-scale linear systems. However, these methods usually fa…

math.OC2022

Revisiting Linearized Bregman Iterations under Lipschitz-like Convexity Condition

Hui Zhang, Lu Zhang, Hao-Xing Yang

The linearized Bregman iterations (LBreI) and its variants have received considerable attention in signal/image processing and compressed sensing. Recently, LBreI has been extended…

math.NA2021★ 15 cited

Adaptively Sketched Bregman Projection Methods for Linear Systems

Ziyang Yuan, Lu Zhang, Hongxia Wang +1

The sketch-and-project, as a general archetypal algorithm for solving linear systems, unifies a variety of randomized iterative methods such as the randomized Kaczmarz and randomiz…

math.OC2021

New insights in smoothness and strong convexity with improved convergence of gradient descent

Lu Zhang, Jiani Wang, Hui Zhang

The starting assumptions to study the convergence and complexity of gradient-type methods may be the smoothness (also called Lipschitz continuity of gradient) and the strong convex…