Mathematical programming problems dealing with functions, each of which can be
represented as a difference of two convex functions, are called DC programming problems …

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 …

Over the past several decades, the optimization over the efficient set has seen a substantial
development. The aim of this paper is to provide a state-of-the-art survey of the …

Bilevel optimization problems are hierarchical optimization problems where the feasible
region of the so-called upper level problem is restricted by the graph of the solution set …

This paper is devoted to a thorough study on convex analysis approach to dc (difference of
convex functions) programming and gives the State of the Art. Main results about dc duality …

The DC programming and its DC algorithm (DCA) address the problem of minimizing a
function f= g− h (with g, h being lower semicontinuous proper convex functions on R n) on …

The boosted difference of convex functions algorithm (BDCA) was recently proposed for
minimizing smooth difference of convex (DC) functions. BDCA accelerates the convergence …

We introduce two new algorithms to minimise smooth difference of convex (DC) functions
that accelerate the convergence of the classical DC algorithm (DCA). We prove that the point …

The ramp loss is a robust but non-convex loss for classification. Compared with other non-
convex losses, a local minimum of the ramp loss can be effectively found. The effectiveness …