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arxiv: 1806.02740 · v3 · pith:ILTHYY4Qnew · submitted 2018-06-07 · 🧮 math.ST · math.MG· math.PR· stat.TH

Convergence rates for empirical barycenters in metric spaces: curvature, convexity and extendible geodesics

classification 🧮 math.ST math.MGmath.PRstat.TH
keywords empiricalvarianceinequalitiesmetricspacesbarycentersconvergenceconvexity
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This paper provides rates of convergence for empirical (generalised) barycenters on compact geodesic metric spaces under general conditions using empirical processes techniques. Our main assumption is termed a variance inequality and provides a strong connection between usual assumptions in the field of empirical processes and central concepts of metric geometry. We study the validity of variance inequalities in spaces of non-positive and non-negative Aleksandrov curvature. In this last scenario, we show that variance inequalities hold provided geodesics, emanating from a barycenter, can be extended by a constant factor. We also relate variance inequalities to strong geodesic convexity. While not restricted to this setting, our results are largely discussed in the context of the $2$-Wasserstein space.

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  1. A note on flatness of non separable tangent cone

    math.MG 2019-06 unverdicted novelty 4.0

    In Alexandrov spaces with curvature bounded below, the pushforward of a probability measure to the tangent cone at its barycenter has support contained in a Hilbert space without requiring separability of the cone.