Orateur
Csaba Fabian
(John von Neumann University)
Description
Gradient computation of multivariate distribution functions calls for a considerable effort. Hence coordinate descent and derivative-free approaches are attractive. This talk deals with constrained convex problems. We perform random descent steps in an approximation scheme that is an inexact cutting-plane method from a dual viewpoint. We prove that the scheme converges and present a computational study comparing different descent methods applied in the approximation scheme.
Authors
Csaba Fabian
(John von Neumann University)
Edit Csizmás
(John von Neumann University)
Rajmund Drenyovszki
(John von Neumann University)
Tamás Szántai
(Budapest University of Technology and Economics)
