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CVPR
2012
IEEE
12 years 1 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
ASUNAM
2011
IEEE
12 years 10 months ago
Evolutionary Clustering and Analysis of Bibliographic Networks
—In this paper, we study the problem of evolutionary clustering of multi-typed objects in a heterogeneous bibliographic network. The traditional methods of homogeneous clustering...
Manish Gupta, Charu C. Aggarwal, Jiawei Han, Yizho...
COLT
2004
Springer
14 years 4 months ago
On the Convergence of Spectral Clustering on Random Samples: The Normalized Case
Given a set of n randomly drawn sample points, spectral clustering in its simplest form uses the second eigenvector of the graph Laplacian matrix, constructed on the similarity gra...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
PAMI
2007
113views more  PAMI 2007»
13 years 10 months ago
Dominant Sets and Pairwise Clustering
—We develop a new graph-theoretic approach for pairwise data clustering which is motivated by the analogies between the intuitive concept of a cluster and that of a dominant set ...
Massimiliano Pavan, Marcello Pelillo
MST
2010
107views more  MST 2010»
13 years 9 months ago
Fixed-Parameter Algorithms for Cluster Vertex Deletion
We initiate the first systematic study of the NP-hard Cluster Vertex Deletion (CVD) problem (unweighted and weighted) in terms of fixed-parameter algorithmics. In the unweighted...
Falk Hüffner, Christian Komusiewicz, Hannes M...