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- W3033641569 abstract "Given a discrete probability measure supported on $N$ atoms and a set of $n$ real-valued functions, there exists a probability measure that is supported on a subset of $n+1$ of the original $N$ atoms and has the same mean when integrated against each of the $n$ functions. If $ N gg n$ this results in a huge reduction of complexity. We give a simple geometric characterization of barycenters via negative cones and derive a randomized algorithm that computes this new measure by greedy geometric sampling. We then study its properties, and benchmark it on synthetic and real-world data to show that it can be very beneficial in the $Ngg n$ regime. A Python implementation is available at url{this https URL}." @default.
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- W3033641569 date "2020-06-02" @default.
- W3033641569 modified "2023-09-27" @default.
- W3033641569 title "A Randomized Algorithm to Reduce the Support of Discrete Measures" @default.
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