An Analytical Formula for Spectrum Reconstruction
Probability
2020-06-02 v1 Machine Learning
Abstract
We study the spectrum reconstruction technique. As is known to all, eigenvalues play an important role in many research fields and are foundation to many practical techniques such like PCA(Principal Component Analysis). We believe that related algorithms should perform better with more accurate spectrum estimation. There was an approximation formula proposed, however, they didn't give any proof. In our research, we show why the formula works. And when both number of features and dimension of space go to infinity, we find the order of error for the approximation formula, which is related to a constant -the ratio of dimension of space and number of features.
Cite
@article{arxiv.2006.00152,
title = {An Analytical Formula for Spectrum Reconstruction},
author = {Zhibo Dai and Heinrich Matzinger and Ionel Popescu},
journal= {arXiv preprint arXiv:2006.00152},
year = {2020}
}