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PAMI
2007
202views more  PAMI 2007»
14 years 9 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
SCIA
2009
Springer
146views Image Analysis» more  SCIA 2009»
15 years 4 months ago
Extraction of Windows in Facade Using Kernel on Graph of Contours
In the past few years, street-level geoviewers has become a very popular web-application. In this paper, we focus on a first urban concept which has been identified as useful for...
Jean-Emmanuel Haugeard, Sylvie Philipp-Foliguet, F...
PAMI
2010
103views more  PAMI 2010»
14 years 8 months ago
The Sum-over-Paths Covariance Kernel: A Novel Covariance Measure between Nodes of a Directed Graph
—This work introduces a link-based covariance measure between the nodes of a weighted directed graph where a cost is associated to each arc. To this end, a probability distributi...
Amin Mantrach, Luh Yen, Jérôme Callut...
CIKM
2009
Springer
15 years 4 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
ICASSP
2011
IEEE
14 years 1 months ago
Polytope kernel density estimates on Delaunay graphs
We present a polytope-kernel density estimation (PKDE) methodology that allows us to perform exact mean-shift updates along the edges of the Delaunay graph of the data. We discuss...
Erhan Bas, Deniz Erdogmus