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NIPS
2008
14 years 11 months ago
Spectral Clustering with Perturbed Data
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...
ICML
2005
IEEE
15 years 10 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
NIPS
2003
14 years 11 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
15 years 3 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
JIPS
2007
103views more  JIPS 2007»
14 years 9 months ago
Feature Extraction of Concepts by Independent Component Analysis
: Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the f...
Altangerel Chagnaa, Cheolyoung Ock, Chang Beom Lee...