Generalized conditional gradient: analysis of convergence and applications
Machine Learning
2015-11-20 v1 Optimization and Control
Machine Learning
Abstract
The objectives of this technical report is to provide additional results on the generalized conditional gradient methods introduced by Bredies et al. [BLM05]. Indeed , when the objective function is smooth, we provide a novel certificate of optimality and we show that the algorithm has a linear convergence rate. Applications of this algorithm are also discussed.
Cite
@article{arxiv.1510.06567,
title = {Generalized conditional gradient: analysis of convergence and applications},
author = {Alain Rakotomamonjy and Rémi Flamary and Nicolas Courty},
journal= {arXiv preprint arXiv:1510.06567},
year = {2015}
}