Computational complexity of learning algebraic varieties
Algebraic Geometry
2020-10-19 v2 Machine Learning
Abstract
We analyze the complexity of fitting a variety, coming from a class of varieties, to a configuration of points in . The complexity measure, called the algebraic complexity, computes the Euclidean Distance Degree (EDdegree) of a certain variety called the hypothesis variety as the number of points in the configuration increases. For the problem of fitting an -sphere to a configuration of points in , we give a closed formula of the algebraic complexity of the hypothesis variety as grows for the case of . For the case we conjecture a generalization of this formula supported by numerical experiments.
Cite
@article{arxiv.1910.03305,
title = {Computational complexity of learning algebraic varieties},
author = {Oliver Gäfvert},
journal= {arXiv preprint arXiv:1910.03305},
year = {2020}
}