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» Clustering the Feature Space
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ICML
2007
IEEE
16 years 7 months ago
Entire regularization paths for graph data
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda
ICML
2006
IEEE
16 years 7 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ICML
2006
IEEE
16 years 7 months ago
Optimal kernel selection in Kernel Fisher discriminant analysis
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
ICML
2006
IEEE
16 years 7 months ago
Semi-supervised nonlinear dimensionality reduction
The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlo...
ICML
2005
IEEE
16 years 7 months ago
Weighted decomposition kernels
We introduce a family of kernels on discrete data structures within the general class of decomposition kernels. A weighted decomposition kernel (WDK) is computed by dividing objec...
Sauro Menchetti, Fabrizio Costa, Paolo Frasconi