A survey of optimization approaches for wireless physical layer security
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 …
increasing concerns from both academia and industry. The research on physical layer …
DC programming and DCA: thirty years of developments
HA Le Thi, T Pham Dinh - Mathematical Programming, 2018 - Springer
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 …
Open issues and recent advances in DC programming and DCA
HA Le Thi, T Pham Dinh - Journal of Global Optimization, 2024 - Springer
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 …
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 …
An improved column generation algorithm for minimum sum-of-squares clustering
Given a set of entities associated with points in Euclidean space, minimum sum-of-squares
clustering (MSSC) consists in partitioning this set into clusters such that the sum of squared …
clustering (MSSC) consists in partitioning this set into clusters such that the sum of squared …
Qualitative properties of the minimum sum-of-squares clustering problem
Fundamental qualitative properties of the minimum sum-of-squares clustering problem are
established in this paper. We prove that the problem always has a global solution and …
established in this paper. We prove that the problem always has a global solution and …
Feature selection in machine learning: an exact penalty approach using a difference of convex function algorithm
We develop an exact penalty approach for feature selection in machine learning via the zero-
norm ℓ _ 0 ℓ 0-regularization problem. Using a new result on exact penalty techniques we …
norm ℓ _ 0 ℓ 0-regularization problem. Using a new result on exact penalty techniques we …
A DC programming approach for feature selection in support vector machines learning
Feature selection consists of choosing a subset of available features that capture the
relevant properties of the data. In supervised pattern classification, a good choice of features …
relevant properties of the data. In supervised pattern classification, a good choice of features …
Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems
This paper introduces an algorithm for solving the minimum sum-of-squares clustering
problems using their difference of convex representations. A non-smooth non-convex …
problems using their difference of convex representations. A non-smooth non-convex …
New and efficient DCA based algorithms for minimum sum-of-squares clustering
PD Tao - Pattern Recognition, 2014 - Elsevier
The purpose of this paper is to develop new efficient approaches based on DC (Difference
of Convex functions) programming and DCA (DC Algorithm) to perform clustering via …
of Convex functions) programming and DCA (DC Algorithm) to perform clustering via …