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» On Clusterings - Good, Bad and Spectral
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ICASSP
2010
IEEE
13 years 7 months ago
Evolutionary spectral clustering with adaptive forgetting factor
Many practical applications of clustering involve data collected over time. In these applications, evolutionary clustering can be applied to the data to track changes in clusters ...
Kevin S. Xu, Mark Kliger, Alfred O. Hero III
IWCMC
2010
ACM
14 years 13 days ago
Group detection in mobility traces
—Analysis and modeling of wireless networks greatly depend on understanding the structure of underlying mobile nodes. In this paper we present two clustering algorithms to determ...
Yung-Chih Chen, Elisha J. Rosensweig, Jim Kurose, ...
SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
13 years 8 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...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 7 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
11 years 9 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...