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ICPR
2008
IEEE
14 years 10 months ago
Combining content and structure similarity for XML document classification using composite SVM kernels
Combination of structure and content features is necessary for effective retrieval and classification of XML documents. Composite kernels provide a way for fusion of content and s...
Pabitra Mitra, Saptarshi Ghosh
COLT
2007
Springer
14 years 3 months ago
How Good Is a Kernel When Used as a Similarity Measure?
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
Nathan Srebro
ICTIR
2009
Springer
14 years 3 months ago
Robust Word Similarity Estimation Using Perturbation Kernels
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...
Kevyn Collins-Thompson
ICDM
2006
IEEE
133views Data Mining» more  ICDM 2006»
14 years 3 months ago
An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph, namely the exponential diffusion kernel, the Laplacian diffusion kernel, the ...
François Fouss, Luh Yen, Alain Pirotte, Mar...
ML
2008
ACM
110views Machine Learning» more  ML 2008»
13 years 7 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro