paper

Random Polytope Descriptors

arXiv:2009.13987

Abstract

We introduce a class of random polytopes which simultaneously generalizes several known constructions. While being fairly general, these polytopes are also computationally exceptionally benign. We indicate how these properties can be exploited for classification and clustering tasks in data analysis. Crucially, our construction lets users smoothly trade off between a tighter description of the data and faster computation.

19 pages (v3); major rewrite (new title, more stochastic geometry, less machine learning); experiments reworked from scratch; code and data available on zenodo, doi:10.5281/zenodo.22913313

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