1 citations · 2 across the 8 of their papers we have counts for
12 papers
A stochastic three-block splitting algorithm and its application to quantized deep neural networks
Fengmiao Bian, Ren Liu, Xiaoqun Zhang
Deep neural networks (DNNs) have made great progress in various fields. In particular, the quantized neural network is a promising technique making DNNs compatible on resource-limi…
Low-Rank and Framelet Based Sparsity Decomposition for Interventional MRI Reconstruction
Zhao He, Ya-Nan Zhu, Suhao Qiu +2
Objective: Interventional MRI (i-MRI) is crucial for MR image-guided therapy. Current image reconstruction methods for dynamic MR imaging are mostly retrospective that may not be s…
A Stochastic Alternating Direction Method of Multipliers for Non-smooth and Non-convex Optimization
Fengmiao Bian, Jingwei Liang, Xiaoqun Zhang
Alternating direction method of multipliers (ADMM) is a popular first-order method owing to its simplicity and efficiency. However, similar to other proximal splitting methods, the…
A Stochastic Variance Reduced Primal Dual Fixed Point Method For Linearly Constrained Separable Optimization
Ya-Nan Zhu, Xiaoqun Zhang
In this paper we combine the stochastic variance reduced gradient (SVRG) method [17] with the primal dual fixed point method (PDFP) proposed in [7] to solve a sum of two convex fun…
A three-operator splitting algorithm for nonconvex sparsity regularization
Fengmiao Bian, Xiaoqun Zhang
Sparsity regularization has been largely applied in many fields, such as signal and image processing and machine learning. In this paper, we mainly consider nonconvex minimization…
Stochastic primal dual fixed point method for composite optimization
YaNanZhu, XiaoqunZhang
In this paper we propose a stochastic primal dual fixed point method (SPDFP) for solving the sum of two proper lower semi-continuous convex function and one of which is composite.…