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JCT
2008
85views more  JCT 2008»
13 years 4 months ago
Smith normal form and Laplacians
Let M denote the Laplacian matrix of a graph G. Associated with G is a finite group (G), obtained from the Smith normal form of M, and whose order is the number of spanning trees o...
Dino J. Lorenzini
COLT
2004
Springer
13 years 10 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...
FCS
2006
13 years 6 months ago
The Representational Power of Conjunctive Normal Form
- There is continuing research interest in comparison of the complexity of problems within the class NP-Complete. This paper examines the representational power of conjunctive norm...
Thomas O'Neil, Jason Smith
CVPR
2005
IEEE
14 years 6 months ago
Corrected Laplacians: Closer Cuts and Segmentation with Shape Priors
We optimize over the set of corrected laplacians (CL) associated with a weighted graph to improve the average case normalized cut (NCut) of a graph. Unlike edge-relaxation SDPs, o...
David Tolliver, Gary L. Miller, Robert T. Collins
JMLR
2008
79views more  JMLR 2008»
13 years 4 months ago
Manifold Learning: The Price of Normalization
We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consis...
Yair Goldberg, Alon Zakai, Dan Kushnir, Yaacov Rit...