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A new discriminative kernel from probabilistic models

Tsuda, Koji; Kawanabe, M; Raetsch, Gunnar; Sonnenburg, Soren; Mueller, Klaus-Robert

Description

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully

CollectionsANU Research Publications
Date published: 2002
Type: Journal article
URI: http://hdl.handle.net/1885/72038
Source: Neural Computation
DOI: 10.1162/08997660260293274

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