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On the noise sensitivity of monotone functions

Authors: Mossel, Elchanan; O'Donnell, Ryan;

On the noise sensitivity of monotone functions

Abstract

AbstractIt is known that for all monotone functions f : {0, 1}n → {0, 1}, if x ∈ {0, 1}n is chosen uniformly at random and y is obtained from x by flipping each of the bits of x independently with probability ϵ = n−α, then P[f(x) ≠ f(y)] < cn−α+1/2, for some c > 0.Previously, the best construction of monotone functions satisfying P[fn(x) ≠ fn(y)] ≥ δ, where 0 < δ < 1/2, required ϵ ≥ c(δ)n−α, where α = 1 − ln 2/ln 3 = 0.36907 …, and c(δ) > 0. We improve this result by achieving for every 0 < δ < 1/2, P[fn(x) ≠ fn(y)] ≥ δ, with: ϵ = c(δ)n−α for any α < 1/2, using the recursive majority function with arity k = k(α); ϵ = c(δ)n−1/2logtn for t = log2 $$\sqrt{\pi / 2}$$ = .3257 …, using an explicit recursive majority function with increasing arities; and ϵ = c(δ)n−1/2, nonconstructively, following a probabilistic CNF construction due to Talagrand. We also study the problem of achieving the best dependence on δ in the case that the noise rate ϵ is at least a small constant; the results we obtain are tight to within logarithmic factors. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 23: 333–350, 2003

Keywords

Statistics and Probability, FOS: Computer and information sciences, Learning and adaptive systems in artificial intelligence, 511, Computational learning theory, 89999 Information and Computing Sciences not elsewhere classified, Boolean functions

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Average
Top 10%
Top 10%
bronze