The Limit of One-Class SVM

author: Regis Vert, University of Paris-Sud 11
published: Feb. 25, 2007,   recorded: October 2005,   views: 9840


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


In this talk, I will present an analysis of the asymptotic behaviour of the One-Class support vector machine (SVM), a popular algorithm for outlier detection. I will show that One-Class SVM asymptotically estimates a truncated version of the density of the distribution generating the data, in the case where the Gaussian kernel is used with a well-calibrated decreasing bandwidth parameter, and the regularization parameter involved in the algorithm is held fixed as the training sample size goes to infinity.A long version of this work can be found at , in which extensions to the 2-class case and to more general convex loss functions are considered.

See Also:

Download slides icon Download slides: EurandomOct05.pdf (124.2┬áKB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 Anthony Brew, March 21, 2008 at 5:29 p.m.:

Any chance of getting this in a non Windows format?

Write your own review or comment:

make sure you have javascript enabled or clear this field: