arXiv:1206.3270 [cs.LG]AbstractReferencesReviewsResources
Estimation and Clustering with Infinite Rankings
Published 2012-06-13Version 1
This paper presents a natural extension of stagewise ranking to the the case of infinitely many items. We introduce the infinite generalized Mallows model (IGM), describe its properties and give procedures to estimate it from data. For estimation of multimodal distributions we introduce the Exponential-Blurring-Mean-Shift nonparametric clustering algorithm. The experiments highlight the properties of the new model and demonstrate that infinite models can be simple, elegant and practical.
Comments: Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI2008)
Keywords: infinite rankings, estimation, infinite generalized mallows model, exponential-blurring-mean-shift nonparametric clustering algorithm, properties
Tags: conference paper
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