%0 Journal Article
%T A Hybrid Algorithm for Convex Semidefinite Optimization
%A Soeren Laue
%J Computer Science
%D 2012
%I arXiv
%X We present a hybrid algorithm for optimizing a convex, smooth function over the cone of positive semidefinite matrices. Our algorithm converges to the global optimal solution and can be used to solve general large-scale semidefinite programs and hence can be readily applied to a variety of machine learning problems. We show experimental results on three machine learning problems (matrix completion, metric learning, and sparse PCA) . Our approach outperforms state-of-the-art algorithms.
%U http://arxiv.org/abs/1206.4608v1