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Joint Training of Deep Boltzmann Machines
Ian Goodfellow, Aaron Courville, Yoshua Bengio
We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at…
Disentangling Factors of Variation via Generative Entangling
Guillaume Desjardins, Aaron Courville, Yoshua Bengio
Here we propose a novel model family with the objective of learning to disentangle the factors of variation in data. Our approach is based on the spike-and-slab restricted Boltzman…
Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery
Ian J. Goodfellow, Aaron Courville, Yoshua Bengio
We consider the problem of using a factor model we call {\em spike-and-slab sparse coding} (S3C) to learn features for a classification task. The S3C model resembles both the spike…