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K. Nguyễn

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#machine learning Preprint Sep 2026

Sliced Orlicz-Wasserstein

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 $\phi$. First, we prove that SOW distance is a metric on the space of measures with finite Orlicz norm, and show t...

B. Tran, K. Nguyễn · 0 citations