Structured prediction using energy-based models
Add to your list(s)
Download to your calendar using vCal
If you have a question about this talk, please contact Shakir Mohamed.
I will cover:
Yann LeCun, Sumit Chopra, Raia Hadsell, Ranzato Marc’Aurelio and Fu-Jie Huang: A Tutorial on Energy-Based Learning, in Bakir, G. and Hofman, T. and Schölkopf, B. and Smola, A. and Taskar, B. (Eds), Predicting Structured Data, MIT Press, 2006
http://yann.lecun.com/exdb/publis/pdf/lecun-06.pdf
LeCun’s “Energy-Based Models” provide a unifying framework for several structured prediction approaches (with an intuitive motivation suitable to engineering new systems). I will use this tutorial paper to introduce a few key ideas of structured prediction. I will also go over a few aspects that LeCun is glossing over in his presentation (regularization e.g.).
Section 8 is particularly interesting for food for thoughts on different approaches…
More info on energy-based models with slides, videos, etc. can be found at: http://www.cs.nyu.edu/~yann/research/ebm/
This talk is part of the Machine Learning Reading Group @ CUED series.
This talk is included in these lists:
Note that ex-directory lists are not shown.
|