## Lecture 14: Approximating Probability Distributions (IV): Variational Methods

author: David MacKay,
University of Cambridge

produced by: David MacKay (University of Cambridge)

author: David MacKay, University of Cambridge

published: Nov. 5, 2012, recorded: July 2012, views: 1598

produced by: David MacKay (University of Cambridge)

author: David MacKay, University of Cambridge

published: Nov. 5, 2012, recorded: July 2012, views: 1598

# 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**to describe your request and upload the data.**

__ticket system__*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:

Sonam Singh, June 5, 2015 at 6:58 p.m.:I copied this question from youtube on same lecture but I am not sure either what is the answer for this question:

The sum of a discrete probability distribution should always be 1, correct? For the distribution shown at 6:00, sum_x Q(x) = 1+epsilon which doesn't equal 1.

Somebody please answer if we are missing something?

Vik Kamath, June 13, 2015 at 1:28 a.m.:@Sonam Singh : You can think of it as P(x) = {0.33,0.33,0.33,\epsilon}

## Write your own review or comment: