Active Support Vector Machine Home Page

Olvi L. Mangasarian
David R. Musicant


LSVM is a fast technique for training support vector machines (SVMs), based on a simple iterative approach. For example, it has been used to classify a dataset with 2 million points and 10 features in only 34 minutes on a 400 Mhz Pentium II. For more information, see our paper Lagrangian Support Vector Machines.

SVMs are optimization based tools for solving machine learning problems. For an introduction to SVMs, you may want to look at this tutorial.

The software is free for academic and research use. For commercial use, please contact Olvi Mangasarian or Dave Musicant.

Click here to download the software, which consists of MATLAB m-files.

If you publish any work based on LSVM, please cite both the software and the paper on which it is based. Here are recommended LaTeX bibliography entries:

author = "O.L. Mangasarian and D. R. Musicant",
title = {{LSVM Software:} Active Set Support Vector Machine Classification Software},
year = 2000,
institution = {Computer Sciences Department, University of Wisconsin, Madison},
note = {$\sim$musicant/lsvm/.}}

author = "O. L. Mangasarian and David R. Musicant",
title = "Lagrangian Support Vector Machine Classification",
institution = "Data Mining Institute, Computer Sciences Department, University of Wisconsin",
month = {June},
year = 2000,
number = {00-06},
address = "Madison, Wisconsin",

For more information, contact:
Olvi L. Mangasarian
David R. Musicant