
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
Statistics and Probability, Other information and computing sciences not elsewhere classified, Learning and adaptive systems in artificial intelligence, 511, Computational learning theory, Boolean functions
Statistics and Probability, Other information and computing sciences not elsewhere classified, Learning and adaptive systems in artificial intelligence, 511, Computational learning theory, Boolean functions
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