Fooling Gaussian PTFs via Local Hyperconcentration
Computational Complexity
2022-02-10 v2
Abstract
We give a pseudorandom generator that fools degree- polynomial threshold functions over -dimensional Gaussian space with seed length . All previous generators had a seed length with at least a dependence on . The key new ingredient is a Local Hyperconcentration Theorem, which shows that every degree- Gaussian polynomial is hyperconcentrated almost everywhere at scale .
Keywords
Cite
@article{arxiv.2103.07809,
title = {Fooling Gaussian PTFs via Local Hyperconcentration},
author = {Ryan O'Donnell and Rocco A. Servedio and Li-Yang Tan and Daniel Kane},
journal= {arXiv preprint arXiv:2103.07809},
year = {2022}
}
Comments
Added mention of independent and concurrent work of Kelley and Meka