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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...
ICML
2009
IEEE
14 years 11 months ago
Multi-instance learning by treating instances as non-I.I.D. samples
Previous studies on multi-instance learning typically treated instances in the bags as independently and identically distributed. The instances in a bag, however, are rarely indep...
Zhi-Hua Zhou, Yu-Yin Sun, Yu-Feng Li
PAMI
1998
107views more  PAMI 1998»
13 years 10 months ago
Graph Matching With a Dual-Step EM Algorithm
—This paper describes a new approach to matching geometric structure in 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifyi...
Andrew D. J. Cross, Edwin R. Hancock
CORR
2010
Springer
176views Education» more  CORR 2010»
13 years 11 months ago
A General Framework for Graph Sparsification
Given a weighted graph G and an error parameter > 0, the graph sparsification problem requires sampling edges in G and giving the sampled edges appropriate weights to obtain a...
Ramesh Hariharan, Debmalya Panigrahi

Publication
203views
13 years 11 months ago
Multigraph Sampling of Online Social Networks
State-of-the-art techniques for probability sampling of users of online social networks (OSNs) are based on random walks on a single social relation. While powerful, these methods ...
Minas Gjoka, Carter T. Butts, Maciej Kurant, Athin...