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Structured prediction using energy-based models

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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.

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