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Abstract: Clustering and dimensionality reduction are simple, effective ways to derive useful representations of data, such as images. These procedures often are used as preprocessing steps for more sophisticated pattern analysis techniques. (In fact, these procedures often perform as well as or better than more sophisticated pattern analysis techniques.) However, in situations where each input has been randomly transformed (e.g., by translation, rotation and shearing in images), these methods tend to... (Update)
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BibTeX entry: (Update)
B. J. Frey and N. Jojic. Transformation-invariant clustering and dimensionality reduction. Submitted to IEEE Transaction on Pattern Analysis and Machine Intelligence, 2000. http://citeseer.ist.psu.edu/frey00transformationinvariant.html More
@misc{ frey00transformationinvariant,
author = "B. Frey and N. Jojic",
title = "Transformation-invariant clustering and dimensionality reduction",
text = "B. J. Frey and N. Jojic. Transformation-invariant clustering and dimensionality
reduction. Submitted to IEEE Transaction on Pattern Analysis and Machine
Intelligence, 2000.",
year = "2000",
url = "citeseer.ist.psu.edu/frey00transformationinvariant.html" }
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