Empirische Inferenz
Article
2008
Optimization Techniques for Semi-Supervised Support Vector Machines
Empirische Inferenz
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs) are based on applying the margin maximization principle to both labeled and unlabeled examples. Unlike SVMs, their formulation leads to a non-convex optimization problem. A suite of algorithms have recently been proposed for solving S3VMs. This paper reviews key ideas in this literature. The performance and behavior of various S3VMs algorithms is studied together, under a common experimental setting.
| Author(s): | Chapelle, O. and Sindhwani, V. and Keerthi, SS. |
| Journal: | Journal of Machine Learning Research |
| Volume: | 9 |
| Pages: | 203-233 |
| Year: | 2008 |
| Month: | February |
| Day: | 0 |
| Bibtex Type: | Article (article) |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Language: | en |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
| Links: | |
BibTex
@article{5369,
title = {Optimization Techniques for Semi-Supervised Support Vector Machines},
journal = {Journal of Machine Learning Research},
abstract = {Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs) are based on applying the margin maximization principle to both labeled and unlabeled examples. Unlike SVMs, their formulation leads to a non-convex optimization problem. A suite of algorithms have recently been proposed for solving S3VMs. This paper reviews key ideas in this literature. The performance and behavior of various S3VMs algorithms is studied together, under a common experimental setting.},
volume = {9},
pages = {203-233},
organization = {Max-Planck-Gesellschaft},
school = {Biologische Kybernetik},
month = feb,
year = {2008},
slug = {5369},
author = {Chapelle, O. and Sindhwani, V. and Keerthi, SS.},
month_numeric = {2}
}