Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …

The alternating direction method of multipliers (ADMM) has been widely used for solving
structured convex optimization problems. In particular, the ADMM can solve convex …

Nonconvex and nonsmooth optimization problems are frequently encountered in much of
statistics, business, science and engineering, but they are not yet widely recognized as a …

In this work we propose a new splitting technique, namely Asymmetric Forward–Backward–
Adjoint splitting, for solving monotone inclusions involving three terms, a maximally …

The alternating direction method of multipliers (ADMM) is widely used in solving structured
convex optimization problems. Despite its success in practice, the convergence of the …

In this paper, we consider a proximal linearized alternating direction method of multipliers, or
PL-ADMM, for solving linearly constrained nonconvex and possibly nonsmooth optimization …

This paper proposes a new hierarchical approach to learning rate adaptation in gradient
methods, called learning rate optimization (LRO). LRO formulates the learning rate adaption …

This paper proposes a new decentralized transactive energy (TE) market strategy
integrating wholesale and local energy markets through coordinated interactions between …

In this paper, we propose a novel classification scheme for the remotely sensed
hyperspectral image (HSI), namely SP-DLRR, by comprehensively exploring its unique …

Robust principal component analysis (RPCA) has drawn significant attention in the last
decade due to its success in numerous application domains, ranging from bioinformatics …