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» Clustering with Bregman Divergences
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 5 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
IDA
2010
Springer
13 years 3 months ago
Clustering with feature order preferences
We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulati...
Jun Sun, Wenbo Zhao, Jiangwei Xue, Zhiyong Shen, Y...
SDM
2007
SIAM
177views Data Mining» more  SDM 2007»
13 years 6 months ago
Multi-way Clustering on Relation Graphs
A number of real-world domains such as social networks and e-commerce involve heterogeneous data that describes relations between multiple classes of entities. Understanding the n...
Arindam Banerjee, Sugato Basu, Srujana Merugu
SODA
2008
ACM
200views Algorithms» more  SODA 2008»
13 years 6 months ago
Clustering for metric and non-metric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P, our goal is to find a set C of size k such that the s...
Marcel R. Ackermann, Johannes Blömer, Christi...
ECML
2005
Springer
13 years 10 months ago
Fitting the Smallest Enclosing Bregman Ball
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learnin...
Richard Nock, Frank Nielsen