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NIPS
2004
13 years 11 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
ICDM
2009
IEEE
171views Data Mining» more  ICDM 2009»
13 years 7 months ago
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
14 years 10 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry
MICCAI
2005
Springer
14 years 11 months ago
White Matter Tract Clustering and Correspondence in Populations
We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every b...
Lauren O'Donnell, Carl-Fredrik Westin
ICML
2010
IEEE
13 years 11 months ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen