Sign-rank can increase under intersection
ACM Transactions on Computation Theory , Volume 13 - Issue 4 p. 24
The communication class UPPcc is a communication analog of the Turing Machine complexity class PP. It is characterized by a matrix-analytic complexity measure called sign-rank (also called dimension complexity), and is essentially the most powerful communication class against which we know how to prove lower bounds. For a communication problem f, let f Λ f denote the function that evaluates f on two disjoint inputs and outputs the AND of the results. We exhibit a communication problem f with UPPcc(f) = O(log n), and UPPcc(f Λ f) = θ (log2 n). This is the first result showing that UPP communication complexity can increase by more than a constant factor under intersection. We view this as a first step toward showing that UPPcc, the class of problems with polylogarithmic-cost UPP communication protocols, is not closed under intersection. Our result shows that the function class consisting of intersections of two majorities on n bits has dimension complexity nω(log n). This matches an upper bound of (Klivans, O'Donnell, and Servedio, FOCS 2002), who used it to give a quasipolynomial time algorithm for PAC learning intersections of polylogarithmically many majorities. Hence, fundamentally new techniques will be needed to learn this class of functions in polynomial time.
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|ACM Transactions on Computation Theory|
|Quantum algorithms and applications|
|Organisation||Centrum Wiskunde & Informatica, Amsterdam, The Netherlands|
Bun, M, Mande, N.S, & Thaler, J. (2021). Sign-rank can increase under intersection. ACM Transactions on Computation Theory, 13(4). doi:10.1145/3470863