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Kernelized sorting

Quadrianto, Novi; Song, Le; Smola, Alexander

Description

Object matching is a fundamental operation in data analysis. It typically requires the definition of a similarity measure between the classes of objects to be matched. Instead, we develop an approach which is able to perform matching by requiring a similarity measure only within each of the classes. This is achieved by maximizing the dependency between matched pairs of observations by means of the Hilbert-Schmidt Independence Criterion. This problem can be cast as one of maximizing a quadratic...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Journal article
URI: http://hdl.handle.net/1885/63656
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2009.184

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