On the number of modes of Gaussian kernel density estimators
Statistics Theory
2025-11-10 v3 Machine Learning
Statistics Theory
Abstract
We consider the Gaussian kernel density estimator with bandwidth of iid Gaussian samples. Using the Kac-Rice formula and an Edgeworth expansion, we prove that the expected number of modes on the real line scales as as provided for some constant . An impetus behind this investigation is to determine the number of clusters to which Transformers are drawn in a metastable state.
Keywords
Cite
@article{arxiv.2412.09080,
title = {On the number of modes of Gaussian kernel density estimators},
author = {Borjan Geshkovski and Philippe Rigollet and Yihang Sun},
journal= {arXiv preprint arXiv:2412.09080},
year = {2025}
}