Active Learning

author: Sanjoy Dasgupta, Department of Computer Science and Engineering, UC San Diego
author: John Langford, Microsoft Research
published: Aug. 26, 2009,   recorded: June 2009,   views: 4943
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.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 1:06:36
!NOW PLAYING
Watch Part 2
Part 2 59:34
!NOW PLAYING

Description

Active learning is defined by contrast to the passive model of supervised learning where all the labels for learning are obtained without reference to the learning algorithm, while in active learning the learner interactively chooses which data points to label. The hope of active learning is that interaction can substantially reduce the number of labels required, making solving problems via machine learning more practical. This hope is known to be valid in certain special cases, both empirically and theoretically.

Variants of active learning have been investigated over several decades and fields. The focus of this tutorial is on general techniques which are applicable to many problems. At a mathematical level, this corresponds to approaches with provable guarantees under weakest-possible assumptions since real problems are more likely to fit algorithms which work under weak assumptions.

We believe this tutorial should be of broad interest. People working on or using supervised learning are often confronted with the need for more labels, where active learning can help. Similarly, in reinforcement learning, generalizing while interacting in more complex ways is an active research topic. Please join us.

See Also:

Download slides icon Download slides: icml09_dasgupta_langford_actl.pdf (454.2┬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 Javier, June 11, 2010 at 1:01 p.m.:

Where is the second part of this tutorial?

Write your own review or comment:

make sure you have javascript enabled or clear this field: