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Kernels and distances for structured data

Gaertner, Thomas; Lloyd, John; Flach, Peter


This paper brings together two strands of machine learning of increasing importance: kernel methods and highly structured data. We propose a general method for constructing a kernel following the syntactic structure of the data, as defined by its type signature in a higher-order logic. Our main theoretical result is the positive definiteness of any kernel thus defined. We report encouraging experimental results on a range of real-world data sets. By converting our kernel to a distance...[Show more]

CollectionsANU Research Publications
Date published: 2004
Type: Journal article
Source: Machine Learning
DOI: 10.1023/B:MACH.0000039777.23772.30


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