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Sliced Orlicz-Wasserstein

Tran, Binh Thuan et al.
arXiv (All) · Papers
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computationstatistics-theory
We propose sliced Orlicz-Wasserstein (SOW) distance which is a generalization of sliced Wasserstein (SW) distance. SOW replaces the $L^p$ norm in SW with a Luxemburg norm cost induced by an Orlicz function $ϕ$. First, we prove that SOW distance is a metric on the space of measures with finite Orlicz
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