Recently, alternating direction method of multipliers (ADMM) attracts much attentions from
various fields and there are many variant versions tailored for different models. Moreover, its …

In recent years, the rapid growth of active consumers in the distribution networks transforms
the modern power markets' structure more independent, flexible, and distributed …

A large number of imaging problems reduce to the optimization of a cost function, with
typical structural properties. The aim of this paper is to describe the state of the art in …

Linear dimensionality reduction methods are a cornerstone of analyzing high dimensional
data, due to their simple geometric interpretations and typically attractive computational …

Alternating direction methods are a common tool for general mathematical programming
and optimization. These methods have become particularly important in the field of …

The formulation _ x, y~ f (x)+ g (y),\quad subject to Ax+ By= b, min x, yf (x)+ g (y), subject to A
x+ B y= b, where f and g are extended-value convex functions, arises in many application …

This paper introduces a parallel and distributed algorithm for solving the following
minimization problem with linear constraints: minimize~~ &f_1 (x _1)+ ⋯+ f_N (x _N)\subject …

With the growing importance of large network models and enormous training datasets,
GPUs have become increasingly necessary to train neural networks. This is largely because …

Recently, regression analysis has become a popular tool for face recognition. Most existing
regression methods use the one-dimensional, pixel-based error model, which characterizes …

With the increasing data scale in the Industrial Internet of Things, edge computing
coordinated with machine learning is regarded as an effective way to raise the novel latency …