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DC programming and DCA: thirty years of developments
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 …
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …
Variations and extension of the convex–concave procedure
T Lipp, S Boyd - Optimization and Engineering, 2016 - Springer
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 …
convex optimization to find local optima of difference of convex (DC) programming problems …
Open issues and recent advances in DC programming and DCA
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 …
tools for nonsmooth nonconvex optimization. This field was created in 1985 by Pham Dinh …
Integrated sensing and communication assisted mobile edge computing: An energy-efficient design via intelligent reflecting surface
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 …
efficient mobile edge computing (MEC). To address the performance degradation due to …
Parallel and distributed methods for constrained nonconvex optimization—Part I: Theory
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 …
nonconvex smooth function subject to nonconvex smooth constraints, and also consider …
DC approximation approaches for sparse optimization
Sparse optimization refers to an optimization problem involving the zero-norm in objective or
constraints. In this paper, nonconvex approximation approaches for sparse optimization …
constraints. In this paper, nonconvex approximation approaches for sparse optimization …
Computing B-stationary points of nonsmooth DC programs
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 …
digital communication system, in particular, by a secrecy sum-rate maximization problem …
Minimization of transformed penalty: theory, difference of convex function algorithm, and robust application in compressed sensing
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 …
transformed l_1 l 1 (TL1), and its application in compressed sensing (CS). The TL1 penalty …
Otfs vs ofdm: Which is superior in multiuser leo satellite communications
Orthogonal time frequency space (OTFS) modulation, a delay-Doppler (DD) domain
communication scheme exhibiting strong robustness against the Doppler shifts, has the …
communication scheme exhibiting strong robustness against the Doppler shifts, has the …
Learning in repeated auctions
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 …
an industry generating hundreds of billions of dollars a year in revenue. Auction theory has …