On the primal-dual dynamics of Support Vector Machines
Systems and Control
2018-05-03 v1
Abstract
The aim of this paper is to study the convergence of the primal-dual dynamics pertaining to Support Vector Machines (SVM). The optimization routine, used for determining an SVM for classification, is first formulated as a dynamical system. The dynamical system is constructed such that its equilibrium point is the solution to the SVM optimization problem. It is then shown, using passivity theory, that the dynamical system is global asymptotically stable. In other words, the dynamical system converges onto the optimal solution asymptotically, irrespective of the initial condition. Simulations and computations are provided for corroboration.
Cite
@article{arxiv.1805.00699,
title = {On the primal-dual dynamics of Support Vector Machines},
author = {Krishna Chaitanya Kosaraju and Shravan Mohan and Ramkrishna Pasumarthy},
journal= {arXiv preprint arXiv:1805.00699},
year = {2018}
}
Comments
To appear in MTNS 2018