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PR
2008
169views more  PR 2008»
13 years 7 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 months ago
Clustering by weighted cuts in directed graphs
In this paper we formulate spectral clustering in directed graphs as an optimization problem, the objective being a weighted cut in the directed graph. This objective extends seve...
Marina Meila, William Pentney
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 1 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
ICONIP
2008
13 years 9 months ago
Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity
In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
JMLR
2006
108views more  JMLR 2006»
13 years 7 months ago
Learning Spectral Clustering, With Application To Speech Separation
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Francis R. Bach, Michael I. Jordan