
AbstractWe design a nonadaptive algorithm that, given oracle access to a function which is ‐far from monotone, makes poly queries and returns an estimate that, with high probability, is an ‐approximation to the distance of to monotonicity. The analysis of our algorithm relies on an improvement to the directed isoperimetric inequality of Khot, Minzer, and Safra (SIAM J. Comput., 2018). Furthermore, we rule out a poly‐query nonadaptive algorithm that approximates the distance to monotonicity significantly better by showing that, for all constant every nonadaptive ‐approximation algorithm for this problem requires queries. This answers a question of Seshadhri (Property Testing Review, 2014) for the case of nonadaptive algorithms. We obtain our lower bound by proving an analogous bound for erasure‐resilient (and tolerant) testers. Our method also yields the same lower bounds for unateness and being a ‐junta.
FOS: Computer and information sciences, sublinear algorithms, Discrete Mathematics (cs.DM), Randomized algorithms, property testing, tolerant and erasure-resilient testing, Computational Complexity (cs.CC), Computer Science - Computational Complexity, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), analysis of Boolean functions, Boolean functions, Computer Science - Discrete Mathematics
FOS: Computer and information sciences, sublinear algorithms, Discrete Mathematics (cs.DM), Randomized algorithms, property testing, tolerant and erasure-resilient testing, Computational Complexity (cs.CC), Computer Science - Computational Complexity, Computer Science - Data Structures and Algorithms, Data Structures and Algorithms (cs.DS), analysis of Boolean functions, Boolean functions, Computer Science - Discrete Mathematics
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