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Using Fast Weights to Improve Persistent Contrastive Divergence

Using Fast Weights to Improve Persistent Contrastive Divergence. Presented by Tijmen Tieleman Joint work with Geoff Hinton University of Toronto. What this is about. An algorithm for unsupervised learning: modeling data density. Not classification or regression. Using Markov Random Fields

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Using Fast Weights to Improve Persistent Contrastive Divergence