Optimized intrinsic dimension estimator using nearest neighbor graphs

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.

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Kumar Sricharan, Raviv Raich, Alfred O. Hero III
• Keywords: Dimension Estimation, ICASSP 2010, Intrinsic Dimension Estimation, KNN Density, Signal Processing