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» On Clusterings - Good, Bad and Spectral
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AUSAI
2009
Springer
15 years 2 months ago
Adapting Spectral Co-clustering to Documents and Terms Using Latent Semantic Analysis
Abstract. Spectral co-clustering is a generic method of computing coclusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of ...
Laurence A. F. Park, Christopher Leckie, Kotagiri ...
93
Voted
IJCAI
2003
15 years 14 days ago
Spectral Learning
We present a simple, easily implemented spectral learning algorithm which applies equally whether we have no supervisory information, pairwise link constraints, or labeled example...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
TKDE
2012
245views Formal Methods» more  TKDE 2012»
13 years 1 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
85
Voted
ICIP
2007
IEEE
16 years 23 days ago
Abnormal Event Detection from Surveillance Video by Dynamic Hierarchical Clustering
The clustering-based approach for detecting abnormalities in surveillance video requires the appropriate definition of similarity between events. The HMM-based similarity defined ...
Fan Jiang, Ying Wu, Aggelos K. Katsaggelos
65
Voted
NIPS
2003
15 years 13 days ago
Pairwise Clustering and Graphical Models
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss