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» Spectral Clustering with Perturbed Data
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NIPS
2001
15 years 1 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
JMLR
2011
133views more  JMLR 2011»
14 years 6 months ago
Operator Norm Convergence of Spectral Clustering on Level Sets
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
Bruno Pelletier, Pierre Pudlo
NIPS
2001
15 years 1 months ago
Spectral Relaxation for K-means Clustering
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
ICCV
2003
IEEE
16 years 1 months ago
Multiclass Spectral Clustering
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
Stella X. Yu, Jianbo Shi
MM
2004
ACM
99views Multimedia» more  MM 2004»
15 years 5 months ago
Locality preserving clustering for image database
It is important and challenging to make the growing image repositories easy to search and browse. Image clustering is a technique that helps in several ways, including image data ...
Xin Zheng, Deng Cai, Xiaofei He, Wei-Ying Ma, Xuey...