Accurate Image Search Using the Contextual Dissimilarity Measure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Residual variance estimation using a nearest neighbor statistic
Journal of Multivariate Analysis
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate
The Journal of Machine Learning Research
A New Classification Algorithm Using Mutual Nearest Neighbors
GCC '10 Proceedings of the 2010 Ninth International Conference on Grid and Cloud Computing
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
The Journal of Machine Learning Research
Hello neighbor: Accurate object retrieval with k-reciprocal nearest neighbors
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.)
IEEE Transactions on Information Theory
An affine invariant k-nearest neighbor regression estimate
Journal of Multivariate Analysis
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Motivated by promising experimental results, this paper investigates the theoretical properties of a recently proposed nonparametric estimator, called the Mutual Nearest Neighbors rule, which estimates the regression function m(x) = E[Y|X = x] as follows: first identify the k nearest neighbors of x in the sample Dn, then keep only those for which x is itself one of the k nearest neighbors, and finally take the average over the corresponding response variables. We prove that this estimator is consistent and that its rate of convergence is optimal. Since the estimate with the optimal rate of convergence depends on the unknown distribution of the observations, we also present adaptation results by data-splitting.