A4 Article in conference proceedings
An Improved Training Algorithm for the Linear Ranking Support Vector Machine




List of Authors: Airola A, Pahikkala T, Salakoski T
Publication year: 2011
Journal: Lecture Notes in Computer Science
Journal name in source: ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT I
Journal acronym: LECT NOTES COMPUT SC
Volume number: 6791
Number of pages: 8
ISSN: 0302-9743

Abstract
We introduce an O(ms + m log(m)) time complexity method for training the linear ranking support vector machine, where in is the number of training examples, and s the average number of non-zero features per example. The method generalizes the fastest previously known approach, which achieves the same efficiency only in restricted special cases. The excellent scalability of the proposed method is demonstrated experimentally.

Last updated on 2019-29-01 at 10:28