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4 Author(s)
Quadrianto, N. ; Canberra Res. Lab., Australian Nat. Univ., Canberra, ACT, Australia ; Smola, A.J. ; Le Song ; Tuytelaars, T.

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 assignment problem with special structure and we present a simple algorithm for finding a locally optimal solution.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:32 ,  Issue: 10 )