event thumbnail image
Gaussian Processes in Practice Workshop

Gaussian Process Basics

author: David MacKay, University of Cambridge

Description

How on earth can a plain old Gaussian distribution be useful for sophisticated regression and machine learning tasks?

You might be experiencing some problems with Your Video player.
Slides
0:02 Gaussian Process Basics
0:55 Nonlinear regression with neural networks
1:24 References
2:00 Motivation: Machine learning
3:00 Can all this be done with a plain old Gaussian distribution?
3:39 Two-dimensional Gaussian
7:03 Inference
7:26 Inference01
8:32 Another representation
11:28 Another representation01
11:45 Another representation02
13:35 Aha!
17:25 Gaussian quiz
24:08 How do we build Gaussian distribution?
25:25 How the matrix was made
27:32 Extend to more points
29:47 A Gaussian process
34:09 Effect of hyperparameters
37:03 Inference of hyperparameters
48:01 Two-dimensional input space
50:09 Efficient computation (... well, modestly efficient)
52:45 Key computational requirements
54:15 Choosing covariance functions
55:51 \"Squared exponential\"
56:10 Emulate infinite neural netwoks
56:29 GPs for classification
58:19 Connection to standard neural networks
60:17 Gaussian Quiz solutions
60:33 Gaussian processes compared with state-of-the-art nonlinear parametric models

Lecture rating

People found this lecture:
Worth seeing
because it is:
 Valuable and informative
Well presented
Easily understandable
Acceptably recorded
You need to login to cast your vote.

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.

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 Rohan Anil, December 31, 2008 at 1:15 a.m.:

Amazing, must watch
crystal clear!


Comment2 swy, June 11, 2009 at noon:

Video is very good, but can we not use rtmp? I would like to save the video so that I can watch it even when I am offline.


Comment3 zslevi, July 28, 2009 at 11:27 a.m.:

So, is the relation between a covariance and inverse covariance like between posterior and prior distributions?


Comment4 Lee, November 5, 2009 at 12:26 a.m.:

video is good, audio is poor though, hard to understand the speaker. My kingdom for a mic!


Comment5 Flávio Coelho, December 2, 2009 at 3:51 p.m.:

What software is he using to generate the graphics in real-time?


Comment6 gordon anderson, February 1, 2010 at 3:38 a.m.:

Very engaging and intuitive intro to gaussian processes.

Highly recommended.

Write your own review or comment:

make sure you have javascript enabled or clear this field: