Heuristic Approaches for Support Vector Machines with the Ramp Loss

Research output: Contribution to journalJournal article

Recently, Support Vector Machines with the ramp loss (RLM) have attracted attention from the computational point of view. In this technical note, we propose two heuristics, the first one based on solving the continuous relaxation of a Mixed Integer Nonlinear formulation of the RLM and the second one based on the training of an SVM classifier on a reduced dataset identified by an integer linear problem. Our computational results illustrate the ability of our heuristics to handle datasets of much larger size than those previously addressed in the literature

Publication information

Original languageEnglish
JournalOptimization Letters
Issue number3
Pages (from-to)1125-1135
StatePublished - 2014
Externally publishedYes

ID: 40947366