Abstract: A Bayesian definition of surprise is as follows: Given a distribution P over models M and some observed data D, the surprise of D is the Kullback-Liebler divergence from the prior to the posterior:
A good experiment or a good conversation is one that has a high expectation of surprise, E[S(D, M)]. In this meetup we will practice having good conversations by using the strategy “Ask the question whose answer will surprise you most.”
The meetup will begin on Wednesday at 7:30pm. For directions to Zendo, see the mailing list:
Meetup : Berkeley: Information theory and the art of conversation
Discussion article for the meetup : Berkeley: Information theory and the art of conversation
WHEN: 08 May 2013 07:30:00PM (-0700)
WHERE: Berkeley, CA
Abstract: A Bayesian definition of surprise is as follows: Given a distribution P over models M and some observed data D, the surprise of D is the Kullback-Liebler divergence from the prior to the posterior:
http://goo.gl/cKE6w
A good experiment or a good conversation is one that has a high expectation of surprise, E[S(D, M)]. In this meetup we will practice having good conversations by using the strategy “Ask the question whose answer will surprise you most.”
The meetup will begin on Wednesday at 7:30pm. For directions to Zendo, see the mailing list:
http://groups.google.com/group/bayarealesswrong
or call me at:
http://i.imgur.com/Vcafy.png
Discussion article for the meetup : Berkeley: Information theory and the art of conversation