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PAMI
2011
9 months 36 min ago
Parallel Spectral Clustering in Distributed Systems
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers fro...
Wen-Yen Chen, Yangqiu Song, Hongjie Bai, Chih-Jen ...
PR
2008
26views more  PR 2008»
1 years 1 months ago
Robust path-based spectral clustering
Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. ...
Hong Chang, Dit-Yan Yeung
CORR
2007
Springer
26views Education» more  CORR 2007»
1 years 1 months ago
A Tutorial on Spectral Clustering
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algeb...
Ulrike von Luxburg
BMCBI
2010
29views more  BMCBI 2010»
1 years 2 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 ...
HAIS
2010
Springer
1 years 2 months ago
A Hybrid Cluster-Lift Method for the Analysis of Research Activities
A hybrid of two novel methods - additive fuzzy spectral clustering and lifting method over a taxonomy - is applied to analyse the research activities of a department. To be specifi...
Boris Mirkin, Susana Nascimento, Trevor I. Fenner,...
DEXA
2010
Springer
67views Database» more  DEXA 2010»
1 years 3 months ago
Improving Alternative Text Clustering Quality in the Avoiding Bias Task with Spectral and Flat Partition Algorithms
Abstract. The problems of finding alternative clusterings and avoiding bias have gained popularity over the last years. In this paper we put the focus on the quality of these alter...
M. Eduardo Ares, Javier Parapar, Alvaro Barreiro
UAI
2003
1 years 3 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
NIPS
2004
1 years 3 months ago
Self-Tuning Spectral Clustering
We study a number of open issues in spectral clustering: (i) Selecting the appropriate scale of analysis, (ii) Handling multi-scale data, (iii) Clustering with irregular backgroun...
Lihi Zelnik-Manor, Pietro Perona
NIPS
2004
1 years 3 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
SDM
2007
SIAM
39views Data Mining» more  SDM 2007»
1 years 3 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
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