A Fast Incremental Spectral Clustering for Large Data Sets

Spectral clustering is an emerging research topic that has numerous applications, such as data dimension reduction and image segmentation. In spectral clustering, as new data points are added continuously, dynamic data sets are processed in an on-line way to avoid costly re-computation. In this pape...

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Bibliographische Detailangaben

Hauptverfasser:	Tengteng Kong, Ye Tian, Hong Shen
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Algorithm design and analysis Clustering algorithms Eigen-Gap Eigenvalues and eigenfunctions Incremental Laplace equations Representative Point Sparse matrices Spectral Clustering Vectors
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