Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations

E1883115 UNEXPLORED

"Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations" is a research paper that introduces a convolutional deep belief network architecture capable of learning hierarchical, shift-invariant feature representations from large-scale unlabeled data.

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Honglak Lee notableWork Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations
Honglak Lee notableWork Unsupervised Learning of Hierarchical Representations with Convolutional Deep Belief Networks
linked to: Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations