Unsupervised discovery of nonlinear structure using contrastive backpropagation.

We describe a way of modeling high-dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron-like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connec...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Hinton, G, Osindero, S, Welling, M, Teh, Y
Format: Journal article
Język:English
Wydane: 2006

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