Due to the malicious attacks in wireless networks, physical layer security has attracted
increasing concerns from both academia and industry. The research on physical layer …

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 …

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 …

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

We discuss two key problems related to learning and optimization of neural networks: the
computation of the adversarial attack for adversarial robustness and approximate …

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 …