Non-Linear Dimensionality Reduction

Part of Advances in Neural Information Processing Systems 5 (NIPS 1992)

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David DeMers, Garrison Cottrell


A method for creating a non-linear encoder-decoder for multidimensional data with compact representations is presented. The commonly used technique of autoassociation is extended to allow non-linear representations, and an objec(cid:173) tive function which penalizes activations of individual hidden units is shown to result in minimum dimensional encodings with respect to allowable error in reconstruction.