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In 1992 Mansour proved that every size-$s$ DNF formula is Fourier-concentrated on $s^{O(loglog s)}$ coefficients. We improve this to $s^{O(loglog k)}$ where $k$ is the read number of the DNF. Since $k$ is always at most $s$, our bound matches Mansours for all DNFs and strengthens it for small-read ones. The previous best bound for read-$k$ DNFs was $s^{O(k^{3/2})}$. For $k$ up to $tilde{Theta}(loglog s)$, we further improve our bound to the optimal $mathrm{poly}(s)$; previously no such bound was known for any $k = omega_s(1)$. Our techniques involve new connections between the term structure of a DNF, viewed as a set system, and its Fourier spectrum.
Given a Boolean function $f:{-1,1}^nto {-1,1}$, the Fourier distribution assigns probability $widehat{f}(S)^2$ to $Ssubseteq [n]$. The Fourier Entropy-Influence (FEI) conjecture of Friedgut and Kalai asks if there exist a universal constant C>0 such
The problem of constructing pseudorandom generators that fool halfspaces has been studied intensively in recent times. For fooling halfspaces over the hypercube with polynomially small error, the best construction known requires seed-length O(log^2 n
We exhibit an unambiguous k-DNF formula that requires CNF width $tilde{Omega}(k^2)$, which is optimal up to logarithmic factors. As a consequence, we get a near-optimal solution to the Alon--Saks--Seymour problem in graph theory (posed in 1991), whic
Finding cliques in random graphs and the closely related planted clique variant, where a clique of size t is planted in a random G(n,1/2) graph, have been the focus of substantial study in algorithm design. Despite much effort, the best known polynom
We introduce a method for proving lower bounds on the efficacy of semidefinite programming (SDP) relaxations for combinatorial problems. In particular, we show that the cut, TSP, and stable set polytopes on $n$-vertex graphs are not the linear image