1 Robust inference in multivariate linear regression using difference of two convex functions as the discrepancy measureThe authors consider a general multivariate regression model (1)Y i =X i ' β+E i , where Y
Melzer, D. : ‘On the expressibility of piecewise-linear continuous functions as the difference of two piecewise-linear convex functions’, Math. Program. Stud. 29 (1986), 118–134.D. Melzer. On the expressibility of piecewise-linear continuous functions as the difference of two piecewise-...
DifferenceOfConvex(DC) FunctionsandDCProgramming SongcanChen Outline 1.ABriefHistory 2.DCFunctionsandtheirProperty 3.Someexamples 4.DCProgramming 5.CaseStudy 6.Ournextwork 1.ABriefHistory •1964,HoangTuy,(incidentallyinhisconvex optimizationpaper), •1979,J.F.Toland,Dualityformulation •1985,Pham...
We improve this result by constructing a delta convex function of class $C^1(\Bbb R^2)$ which cannot be represented as a difference of two convex functions differentiable at 0. Further we give an example of a delta convex function differentiable everywhere which is not strictly differentiable...
Two new penalty methods for sparse reconstruction are proposed based on two types of difference of convex functions (DC for short) programming in which the DC objective functions are the difference of l1 and lσ q norms and the difference of l1 and lr norms with r > 1. By introducing a ...
We offer an efficient approach based on difference of convex functions (DC) optimization for self-organizing maps (SOM). We consider SOM as an optimization problem with a nonsmooth, nonconvex energy function and investigated DC programming and DC algorithm (DCA), an innovative approach in nonconve...
An approach to supervised distance metric learning based on difference of convex functions programming - bacnguyencong/DML-dc
1993: On the use of a modified Newton method for nonlinear finite element analysis.Comp. Meth. Appl. Mech. Engrg. 110, 275–283 Hiriart-Urruty J.-B. 1985: Generalized differentiability, duality and optimization for problems dealing with differences of convex functions. In: Ponstein, J. (...
We show that the class of all delta-convex selfmappings of R (differences of two convex functions) enjoys the difference property in the sense of N.G. de Bruijn. The Q-differentiability technique has been applied as a proof tool. (C) 2013 Royal Dutch Mathematical Society (KWG). Published...
摘要: We give a necessary and sufficient condition for a difference of convex (DC, for short) functions, defined on a normed space, to be Lipschitz continuous. Our criterion relies on the intersection of the -subdifferentials of the involved functions....