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 …

Foreground detection is the first step in video surveillance system to detect moving objects.
Recent research on subspace estimation by sparse representation and rank minimization …

In this paper, we analyze the convergence of the alternating direction method of multipliers
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …

The alternating direction method of multipliers (ADMM) is widely used to solve large-scale
linearly constrained optimization problems, convex or nonconvex, in many engineering …

Recently, a tensor nuclear norm (TNN) based method was proposed to solve the tensor
completion problem, which has achieved state-of-the-art performance on image and video …

Multi-view clustering aims to partition data collected from diverse sources based on the
assumption that all views are complete. However, such prior assumption is hardly satisfied …

State estimation in electric power grid is vulnerable to false data injection attacks, and
diagnosing such kind of malicious attacks has significant impacts on ensuring reliable …

The matrix completion problem is to recover a low-rank matrix from a subset of its entries.
The main solution strategy for this problem has been based on nuclear-norm minimization …

We design sparse and block sparse feedback gains that minimize the variance amplification
(ie, the H 2 norm) of distributed systems. Our approach consists of two steps. First, we …

Robust tensor recovery plays an instrumental role in robustifying tensor decompositions for
multilinear data analysis against outliers, gross corruptions, and missing values and has a …