@inproceedings{ec31f1b2fad94a8b82cbd6162ad51ecd,
title = "A randomized algorithm for pairwise clustering",
abstract = "We present a stochastic clustering algorithm based on pairwise similarity of datapoints. Our method extends existing deterministic methods, including agglomerative algorithms, min-cut graph algorithms, and connected components. Thus it provides a common framework for all these methods. Our graph-based method differs from existing stochastic methods which are based on analogy to physical systems. The stochastic nature of our method makes it more robust against noise, including accidental edges and small spurious clusters. We demonstrate the superiority of our algorithm using an example with 3 spiraling bands and a lot of noise.",
author = "Yoram Gdalyahu and Daphna Weinshall and Michael Werman",
year = "1999",
language = "American English",
isbn = "0262112450",
series = "Advances in Neural Information Processing Systems",
publisher = "Neural information processing systems foundation",
pages = "424--430",
booktitle = "Advances in Neural Information Processing Systems 11 - Proceedings of the 1998 Conference, NIPS 1998",
note = "12th Annual Conference on Neural Information Processing Systems, NIPS 1998 ; Conference date: 30-11-1998 Through 05-12-1998",
}