Non-Linear Dimensionality Reduction
Abstract
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.
Cite
Text
DeMers and Cottrell. "Non-Linear Dimensionality Reduction." Neural Information Processing Systems, 1992.Markdown
[DeMers and Cottrell. "Non-Linear Dimensionality Reduction." Neural Information Processing Systems, 1992.](https://mlanthology.org/neurips/1992/demers1992neurips-nonlinear/)BibTeX
@inproceedings{demers1992neurips-nonlinear,
title = {{Non-Linear Dimensionality Reduction}},
author = {DeMers, David and Cottrell, Garrison W.},
booktitle = {Neural Information Processing Systems},
year = {1992},
pages = {580-587},
url = {https://mlanthology.org/neurips/1992/demers1992neurips-nonlinear/}
}