@inproceedings{d027113be4fb4182b2426cbdcbb31485,
title = "Non-Adaptive Proper Learning Polynomials",
abstract = "We give the first polynomial-time non-adaptive proper learning algorithm of Boolean sparse multivariate polynomial under the uniform distribution. Our algorithm, for s-sparse polynomial over n variables, makes q = (s/ϵ)γ(s, ϵ) log n queries where 2.66 ≤ γ(s, ϵ) ≤ 6.922 and runs in {\~O}(n) · poly(s, 1/ϵ) time. We also show that for any ϵ = 1/sO(1) any non-adaptive learning algorithm must make at least (s/ϵ)Ω(1) log n queries. Therefore, the query complexity of our algorithm is also polynomial in the optimal query complexity and optimal in n.",
keywords = "Learning, Polynomial, Testing",
author = "Bshouty, {Nader H.}",
note = "Publisher Copyright: {\textcopyright} Nader H. Bshouty.; 40th International Symposium on Theoretical Aspects of Computer Science, STACS 2023 ; Conference date: 07-03-2023 Through 09-03-2023",
year = "2023",
month = mar,
day = "1",
doi = "https://doi.org/10.4230/LIPIcs.STACS.2023.16",
language = "الإنجليزيّة",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
editor = "Petra Berenbrink and Patricia Bouyer and Anuj Dawar and Kante, {Mamadou Moustapha}",
booktitle = "40th International Symposium on Theoretical Aspects of Computer Science, STACS 2023",
}