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» Kernels and Regularization on Graphs
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155
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ICASSP
2011
IEEE
14 years 7 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
123
Voted
ICANN
2005
Springer
15 years 9 months ago
LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator
This paper presents a new method for the selection of the two hyperparameters of Least Squares Support Vector Machine (LS-SVM) approximators with Gaussian Kernels. The two hyperpar...
Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel ...
132
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ISBRA
2007
Springer
15 years 9 months ago
Discovering Relations Among GO-Annotated Clusters by Graph Kernel Methods
The biological interpretation of large-scale gene expression data is one of the challenges in current bioinformatics. The state-of-theart approach is to perform clustering and then...
Italo Zoppis, Daniele Merico, Marco Antoniotti, Bu...
176
Voted
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 6 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...
128
Voted
COMBINATORICS
2006
221views more  COMBINATORICS 2006»
15 years 3 months ago
Kernels of Directed Graph Laplacians
Abstract. Let G denote a directed graph with adjacency matrix Q and indegree matrix D. We consider the Kirchhoff matrix L = D - Q, sometimes referred to as the directed Laplacian. ...
John S. Caughman IV, J. J. P. Veerman