Random Mosaics in Machine Learning

Stochastic geometry, at the intersection of convex geometry and probability, is the study of spatial point processes such as random mosaics. Separately, random feature methods are a technique in machine learning used to decrease the computational cost of kernel machines in large-scale problems. In this talk, I will describe the surprising application of random mosaics to random feature methods from research I conducted at the California Institute of Technology; fist, we will investigate the abstract definition and a few examples of random mosaics; next, we will discuss a number of important constructions relating to random mosaics, such as the typical cell and associated zonoid; and finally, I will discuss the particular application of random mosaics that I studied as related to the uniformly rotated Mondrian kernel.

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