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Noise Stability Is Computable and Approximately Low-Dimensional

Authors Anindya De, Elchanan Mossel, Joe Neeman

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  • Gaussian noise stability; Plurality is stablest; Ornstein Uhlenbeck operator

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Abstract

Questions of noise stability play an important role in hardness of approximation in computer science as well as in the theory of voting. In many applications, the goal is to find an optimizer of noise stability among all possible partitions of R^n for n >= 1 to k parts with given Gaussian measures mu_1, ..., mu_k. We call a partition epsilon-optimal, if its noise stability is optimal up to an additive epsilon. In this paper, we give an explicit, computable function n(epsilon) such that an epsilon-optimal partition exists in R^{n(epsilon)}. This result has implications for the computability of certain problems in non-interactive simulation, which are addressed in a subsequent work.

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Anindya De, Elchanan Mossel, and Joe Neeman. Noise Stability Is Computable and Approximately Low-Dimensional. In 32nd Computational Complexity Conference (CCC 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 79, pp. 10:1-10:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017) https://doi.org/10.4230/LIPIcs.CCC.2017.10

Author Details

Anindya De
Elchanan Mossel
Joe Neeman

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