Reductions in Machine Learning

author: Alina Beygelzimer, IBM Thomas J. Watson Research Center
author: Bianca Zadrozny, Computer Science Department, Fluminense Federal University
author: John Langford, Microsoft Research
published: Aug. 26, 2009,   recorded: June 2009,   views: 788
Categories

Slides

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.
  Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 1:34:22
!NOW PLAYING
Watch Part 2
Part 2 34:10
!NOW PLAYING

Description

Machine learning reductions are about reusing solutions to simple, core problems in order to solve more complex problems. A basic difficulty in applying machine learning in practice is that we often need to solve problems that don't quite match the problems solved by standard machine learning algorithms. Reductions are techniques that transform such practical problems into core machine learning problems. These can then be solved using any existing learning algorithm whose solution can, in turn, be used to solve the original problem. The material that we plan to cover is both algorithmic and analytic. We will discuss existing and new algorithms, along with the methodology for analyzing and creating new reductions. We will also discuss common design flaws in folklore reductions. In our experience, this approach is an effective tool for designing empirically successful, automated solutions to learning problems.

See Also:

Download slides icon Download slides: icml09_beygelzimer_zadrozny_langford_riml.pdf (847.1┬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 !

Write your own review or comment:

make sure you have javascript enabled or clear this field: