Lower Bounds on Same-Set Inner Product in Correlated Spaces

Authors Jan Hazla, Thomas Holenstein, Elchanan Mossel

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Jan Hazla
Thomas Holenstein
Elchanan Mossel

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Jan Hazla, Thomas Holenstein, and Elchanan Mossel. Lower Bounds on Same-Set Inner Product in Correlated Spaces. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 60, pp. 34:1-34:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


Let P be a probability distribution over a finite alphabet Omega^L with all L marginals equal. Let X^(1), ..., X^(L), where X^(j) = (X_1^(j), ..., X_n^(j)) be random vectors such that for every coordinate i in [n] the tuples (X_i^(1), ..., X_i^(L)) are i.i.d. according to P. The question we address is: does there exist a function c_P independent of n such that for every f: Omega^n -> [0, 1] with E[f(X^(1))] = m > 0 we have E[f(X^(1)) * ... * f(X^(n))] > c_P(m) > 0? We settle the question for L=2 and when L>2 and P has bounded correlation smaller than 1.
  • same set hitting
  • product spaces
  • correlation
  • lower bounds


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