Abstract :
The sign-rank of a matrix A = [Aij] with plusmn1 entries is the least rank of a real matrix B = [Bij] with AijBij > 0 for all i, j. We obtain the first exponential lower bound on the sign-rank of a function in AC0. Namely, let f(x, y) = Lambdai=1 m Lambdaj=1 m 2(xij Lambda yij). We show that the matrix [f(x, y)]x, y has sign-rank 2Omega(m). This in particular implies that Sigma2 ccnsubeUPPcc, which solves a long-standing open problem posed by Babai, Frankl, and Simon (1986). Our result additionally implies a lower bound in learning theory. Specifically, let Phi1,..., Phir : {0, 1}n rarrRopf be functions such that every DNF formula f : {0, 1}n rarr {-1, +1} of polynomial size has the representation f equiv sign(a1Phi1 + hellip + arPhir) for some reals a1,..., ar. We prove that then r ges 2Omega(n 1/3 ), which essentially matches an upper bound of 2Otilde(n 1/3 ) due to Klivans and Servedio (2001). Finally, our work yields the first exponential lower bound on the size of threshold-of-majority circuits computing a function in AC0. This substantially generalizes and strengthens the results of Krause and Pudlak (1997).
Keywords :
computational complexity; matrix algebra; first exponential lower bound; polynomial size; real matrix; sign-rank; threshold-of-majority circuits; Bismuth; Boolean functions; Circuits; Complexity theory; Computer science; Error correction; Error correction codes; Polynomials; USA Councils; Upper bound; Communication complexity; Complexity classes Sigma_2^cc and UPP^cc; Constant-depth AND/OR/NOT circuits; Multivariate polynomials; Sign-rank;