2022
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
NeurIPS 2022accept
Sliced Wasserstein distances preserve properties of classic Wasserstein distances while being more scalable for computation and estimation in high dimensions. The goal of this work is to quantify this scalability from three key aspects: (i) empirical convergence rates; (ii) robustness to data contam…