Fourier-Information Duality in the Identity Management Problem

Xiaoye Jiang, Jonathan Huang, and Leonidas Guibas
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML 2011), September, 2011.


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Abstract
We compare two recently proposed approaches for representing probability distributions over the space of permutations in the context of multi-target tracking. We show that these two representations, the Fourier approximation and the information form approximation can both be viewed as low dimensional projections of a true distribution, but with respect to different metrics. We identify the strengths and weaknesses of each approximation, and propose an algorithm for converting between the two forms, allowing for a hybrid approach that draws on the strengths of both representations. We show experimental evidence that there are situations where hybrid algorithms are favorable.

Notes
Number of pages: 16

Text Reference
Xiaoye Jiang, Jonathan Huang, and Leonidas Guibas, "Fourier-Information Duality in the Identity Management Problem," The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML 2011), September, 2011.

BibTeX Reference
@inproceedings{Huang_2011_6869,
   author = "Xiaoye Jiang and Jonathan Huang and Leonidas Guibas",
   title = "Fourier-Information Duality in the Identity Management Problem",
   booktitle = "The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML 2011)",
   month = "September",
   year = "2011",
}