@inproceedings{krishnamurthy2015on,
author = {Krishnamurthy, Akshay and Kandasamy, Kirthevasan and Poczos, Barnabas and Wasserman, Larry},
title = {On Estimating L_2^2 Divergence},
booktitle = {Artificial Intelligence and Statistics},
year = {2015},
month = {May},
abstract = {We give a comprehensive theoretical characterization of a nonparametric estimator for the  divergence between two continuous distributions. We first bound the rate of convergence of our estimator, showing that it is \sqrt[n][\latex]-consistent provided the densities are sufficiently smooth. In this smooth regime, we then show that our estimator is asymptotically normal, construct asymptotic confidence intervals, and establish a Berry-Esséen style inequality characterizing the rate of convergence to normality. We also show that this estimator is minimax optimal.},
url = {http://approjects.co.za/?big=en-us/research/publication/on-estimating-l_22-divergence/},
}