Adaptivity to Local Smoothness and Dimension in Kernel Regression

Abstract

We present the first result for kernel regression where the procedure adapts locally at a point x to both the unknown local dimension of the metric and the unknown H\older-continuity of the regression function at x. The result holds with high probability simultaneously at all points x in a metric space of unknown structure."

Tasks

Reproductions