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 …

We investigate the convex–concave procedure, a local heuristic that utilizes the tools of
convex optimization to find local optima of difference of convex (DC) programming problems …

In this two-part paper, we propose a general algorithmic framework for the minimization of a
nonconvex smooth function subject to nonconvex smooth constraints, and also consider …

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 …

In this letter, we propose an integrated sensing and communication (ISAC) assisted energy-
efficient mobile edge computing (MEC). To address the performance degradation due to …

Sparse optimization refers to an optimization problem involving the zero-norm in objective or
constraints. In this paper, nonconvex approximation approaches for sparse optimization …

Motivated by a class of applied problems arising from physical layer based security in a
digital communication system, in particular, by a secrecy sum-rate maximization problem …

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 …

Online auctions are one of the most fundamental facets of the modern economy and power
an industry generating hundreds of billions of dollars a year in revenue. Auction theory has …

This chapter investigates the energy-efficient base station (BS) association and
beamforming for multi-cell multiuser systems. Section 10.1 introduces the motivation of …