Data Clustering by Markovian Relaxation and the Information Bottleneck Method

@inproceedings{Tishby2000DataCB,
  title={Data Clustering by Markovian Relaxation and the Information Bottleneck Method},
  author={Naftali Tishby and Noam Slonim},
  booktitle={NIPS},
  year={2000}
}
We introduce a new, non-parametric and principled, distance based clustering method. This method combines a pairwise based approach with a vector-quantization method which provide a meaningful interpretation to the resulting clusters. The idea is based on turning the distance matrix into a Markov process and then examine the decay of mutual-information during the relaxation of this process. The clusters emerge as quasi-stable structures during this relaxation, and then are extracted using the… CONTINUE READING
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