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Unsupervised discovery of nonlinear structure using contrastive backpropagation.

COGNITIVE SCIENCE, no. 4.0 (2006): 725.0-731.0

引用146|浏览64
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摘要

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 connection weights that determine how the acti...更多

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