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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 2 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICAI
2004
13 years 11 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
PR
2007
116views more  PR 2007»
13 years 9 months ago
GAPS: A clustering method using a new point symmetry-based distance measure
In this paper, an evolutionary clustering technique is described that uses a new point symmetry-based distance measure. The algorithm is therefore able to detect both convex and n...
Sanghamitra Bandyopadhyay, Sriparna Saha
BMCBI
2010
136views more  BMCBI 2010»
13 years 10 months ago
SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale
Background: An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed...
Tamás Nepusz, Rajkumar Sasidharan, Alberto ...
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
14 years 10 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu