The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …

This paper presents a content-centric transmission design in a cloud radio access network
by incorporating multicasting and caching. Users requesting the same content form a …

Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Fully-
immersive VR experience requires the wireless delivery of huge data at ultra-low latency …

This paper considers nonconvex distributed constrained optimization over networks,
modeled as directed (possibly time-varying) graphs. We introduce the first algorithmic …

Mobile relaying has aroused great interest in wireless communications recently, thanks to
the rapid development and evolvement of unmanned aerial vehicles. This letter establishes …

DC (difference of convex functions) programming and DC algorithm (DCA) are powerful
tools for nonsmooth nonconvex optimization. This field was created in 1985 by Pham Dinh …

Mathematical optimization has always been at the heart of engineering, statistics, and
economics. In these applied domains, optimization concepts and methods have often been …

We propose a DC (Difference of two Convex functions) formulation approach for sparse
optimization problems having a cardinality or rank constraint. With the largest-k norm, an …

In this paper, we focus on the constrained sparse regression problem, where the loss
function is convex but nonsmooth and the penalty term is defined by the cardinality function …

We study the minimization problem of a non-convex sparsity promoting penalty function, the
transformed l_1 l 1 (TL1), and its application in compressed sensing (CS). The TL1 penalty …