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. © 2011 Springer-Verlag.
CITATION STYLE
Jiang, X., Huang, J., & Guibas, L. (2011). Fourier-information duality in the identity management problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6912 LNAI, pp. 97–113). https://doi.org/10.1007/978-3-642-23783-6_7
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