TSSort: Probabilistic Noise Resistant Sorting

Jörn Hees; Benjamin Adrian; Ralf Biedert; Thomas Roth-Berghofer; Andreas Dengel

In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1606.05289, Pages 1-10, arXiv, 2016.


In this paper we present TSSort, a probabilistic, noise resistant, quickly converging comparison sort algorithm based on Microsoft TrueSkill. The algorithm combines TrueSkill’s updating rules with a newly developed next item pair selection strategy, enabling it to beat standard sorting algorithms w.r.t. convergence speed and noise resistance, as shown in simulations. TSSort is useful if comparisons of items are expensive or noisy, or if intermediate results shall be approximately ordered.


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1606.05289v1.pdf (pdf, 606 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence