Presentation
Presentation of the exponential families, of the mixtures of such distributions and how to learn it. We then present algorithms to simplify mixture model, using Kullback-Leibler di...
ICDM
2010
IEEE
13 years 9 months ago
2010
IEEE
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
CORR
2006
Springer
13 years 11 months ago
2006
Springer
Abstract--A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functi...
SDM
2004
SIAM
14 years 27 days ago
2004
SIAM
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
KDD
2004
ACM
14 years 12 months ago
2004
ACM
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...