Escaping the curse of dimensionality with a tree-based regressor

Abstract

We present the first tree-based regressor whose convergence rate depends only on the intrinsic dimension of the data, namely its Assouad dimension. The regressor uses the RPtree partitioning procedure, a simple randomized variant of k-d trees.

References in corpus (1)

• Local polynomial regression on unknown manifolds