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Geometric EDA for Random Objects

Paromita Dubey (University of Southern California)
E18-304

Abstract: In this talk I will propose new tools for the exploratory data analysis of data objects taking values in a general separable metric space. First, I will introduce depth profiles, where the depth profile of a point ω in the metric space refers to the distribution of the distances between ω and the data objects. I will describe how depth profiles can be harnessed to define transport ranks, which capture the centrality of each element in the metric space with respect to the…

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MIT Institute for Data, Systems, and Society
Massachusetts Institute of Technology
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