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» Approximation Algorithms for Tensor Clustering
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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 10 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
COCOON
2010
Springer
14 years 20 days ago
Clustering with or without the Approximation
We study algorithms for clustering data that were recently proposed by Balcan, Blum and Gupta in SODA’09 [4] and that have already given rise to two follow-up papers. The input f...
Frans Schalekamp, Michael Yu, Anke van Zuylen
SODA
2001
ACM
147views Algorithms» more  SODA 2001»
13 years 9 months ago
Sublinear time approximate clustering
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...
Nina Mishra, Daniel Oblinger, Leonard Pitt
ISBI
2007
IEEE
14 years 2 months ago
Multivariate Hypothesis Testing of Dti Data for Tissue Clustering
In this work we investigate the feasibility and effectiveness of unsupervised tissue clustering and classification algorithms for DTI data. Tissue clustering and classification ...
Raisa Z. Freidlin, Yaniv Assaf, Peter J. Basser
WIRN
2005
Springer
14 years 1 months ago
Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
Alberto Bertoni, Giorgio Valentini