Hilbert Space Embeddings of Conditional Distributions with Applications to Dynamical Systems

author: Le Song, College of Computing, Georgia Institute of Technology
published: Aug. 26, 2009,   recorded: June 2009,   views: 4909


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 paper, we extend the Hilbert space embedding approach to handle conditional distributions. This leads us to a nonparametric method for modeling dynamical systems, and allows us to update the belief state of a dynamical system by maintaining a conditional embedding. Our method is very general in terms of both the domains and the types of distributions that it can handle, and we demonstrate the effectiveness of our method in various dynamical systems. We expect that Hilbert space embedding of {\em conditional} distributions will have wide applications beyond modeling dynamical systems.

See Also:

Download slides icon Download slides: icml09_song_hsec_01.ppt (3.1┬áMB)

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 Christine Wu, September 2, 2009 at 9:24 p.m.:

The lecture is well presented.

Write your own review or comment:

make sure you have javascript enabled or clear this field: