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Optimized intrinsic dimension estimator using nearest neighbor graphs

TitleOptimized intrinsic dimension estimator using nearest neighbor graphs
Publication TypeConference Paper
Year of Publication2010
AuthorsSricharan, K., R. Raich, and A. O. Hero, III
Conference Name2010 IEEE International Conference on Acoustics, Speech and Signal Processing
Pagination5418 - 5421
Date Published03/2010
PublisherIEEE
Conference LocationDallas, TX
ISBN Number978-1-4244-4295-9
Keywordsgeodesics, intrinsic dimension, k nearest neighbor, kNN density estimation, manifold learning
Abstract

We develop an approach to intrinsic dimension estimation based on k-nearest neighbor (kNN) distances. The dimension estimator is derived using a general theory on functionals of kNN density estimates. This enables us to predict the performance of the dimension estimation algorithm. In addition, it allows for optimization of free parameters in the algorithm. We validate our theory through simulations and compare our estimator to previous kNN based dimensionality estimation approaches.

DOI10.1109/ICASSP.2010.5494931