Manifold estimation and singular deconvolution under Hausdorff loss
Statistics Theory
2012-06-06 v2 Machine Learning
Machine Learning
Statistics Theory
Abstract
We find lower and upper bounds for the risk of estimating a manifold in Hausdorff distance under several models. We also show that there are close connections between manifold estimation and the problem of deconvolving a singular measure.
Keywords
Cite
@article{arxiv.1109.4540,
title = {Manifold estimation and singular deconvolution under Hausdorff loss},
author = {Christopher R. Genovese and Marco Perone-Pacifico and Isabella Verdinelli and Larry Wasserman},
journal= {arXiv preprint arXiv:1109.4540},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.1214/12-AOS994 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)