Where do features come from?

Cognitive Science Society Annual Conference, pp. 1078-1101, 2014.

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Keywords:
boltzmann machinesvariational learninglearning graphical modelsbackpropagationcontrastive divergenceMore(3+)

Abstract:

It is possible to learn multiple layers of non-linear features by backpropagating error derivatives through a feedforward neural network. This is a very effective learning procedure when there is a huge amount of labeled training data, but for many learning tasks very few labeled examples are available. In an effort to overcome the need f...More

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