51 citations · 157 across the 25 of their papers we have counts for
10 papers · 1 filter
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…
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.…
Semi-Implicit Back Propagation
Ren Liu, Xiaoqun Zhang
Neural network has attracted great attention for a long time and many researchers are devoted to improve the effectiveness of neural network training algorithms. Though stochastic…
A parameterized Douglas-Rachford Splitting algorithm for nonconvex optimization
Fengmiao Bian, Xiaoqun Zhang
In this paper, we study a parameterized Douglas-Rachford splitting method for a class of nonconvex optimization problem. A new merit function is constructed to establish the conver…
NLTG Priors in Medical Image: Nonlocal TV-Gaussian (NLTG) prior for Bayesian inverse problems with applications to Limited CT Reconstruction
Didi Lv, Qingping Zhou, Jae Kyu Choi +2
Bayesian inference methods have been widely applied in inverse problems, {largely due to their ability to characterize the uncertainty associated with the estimation results.} {In…
A primal-dual fixed point algorithm for multi-block convex minimization
Peijun Chen, Jianguo Huang, Xiaoqun Zhang
We extend a primal-dual fixed point algorithm (PDFP) proposed in [5] to solve two kinds of separable multi-block minimization problems, arising in signal processing and imaging sci…
A primal-dual fixed-point algorithm for minimization of the sum of three convex separable functions
Peijun Chen, Jianguo Huang, Xiaoqun Zhang
Many problems arising in image processing and signal recovery with multi-regularization can be formulated as minimization of a sum of three convex separable functions. Typically, t…