Sciweavers

281 search results - page 16 / 57
» Graph Kernels
Sort
View
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
IPMU
2010
Springer
14 years 11 months ago
The Link Prediction Problem in Bipartite Networks
We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction functio...
Jérôme Kunegis, Ernesto William De Lu...
ICML
2005
IEEE
15 years 10 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
SMI
2010
IEEE
165views Image Analysis» more  SMI 2010»
14 years 7 months ago
Designing a Topological Modeler Kernel: A Rule-Based Approach
In this article, we present a rule-based language dedicated to topological operations, based on graph transformations. Generalized maps are described as a particular class of graph...
Thomas Bellet, Mathieu Poudret, Agnès Arnou...
ECAI
2008
Springer
14 years 11 months ago
Modeling Collaborative Similarity with the Signed Resistance Distance Kernel
We extend the resistance distance kernel to the domain of signed dissimilarity values, and show how it can be applied to collaborative rating prediction. The resistance distance is...
Jérôme Kunegis, Stephan Schmidt, Sahi...