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Title:

Co-Clustering via information- theoretic Markov aggregation

Document type:
Zeitschriftenaufsatz
Author(s):
Blöchl, C; Amjad, R.A; Geiger, B.C.
Abstract:
We present an information-theoretic cost function for co-clustering, i.e., for simultaneous clustering of two sets based on similarities between their elements. By constructing a simple random walk on the corresponding bipartite graph, our cost function is derived from a recently proposed generalized framework for information-theoretic Markov chain aggregation. The goal of our cost function is to minimize relevant information loss, hence it connects to the information bottleneck formalism. Moreo...     »
Journal title:
IEEE Trans. Knowledge and Data Engineering
Year:
2018
Year / month:
2018-06
Month:
Jun
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1109/TKDE.2018.2846252
Status:
Postprint / reviewed
Submitted:
29.12.2017
Date of publication:
14.06.2018
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