English
Related papers

Related papers: Asymptotically optimal Boolean functions

200 papers

The approximate degree of a Boolean function f is the least degree of a real polynomial that approximates f pointwise to error at most 1/3. Approximate degree is known to be a lower bound on quantum query complexity. We resolve or nearly…

Quantum Physics · Physics 2019-08-20 Mark Bun , Robin Kothari , Justin Thaler

In this paper, we give a quadratic Goldreich-Levin algorithm that is close to optimal in the following ways. Given a bounded function $f$ on the Boolean hypercube $\mathbb{F}_2^n$ and any $\varepsilon>0$, the algorithm returns a quadratic…

Computational Complexity · Computer Science 2025-05-20 Jop Briët , Davi Castro-Silva

List-decodability of Reed-Solomon codes has received a lot of attention, but the best-possible dependence between the parameters is still not well-understood. In this work, we focus on the case where the list-decoding radius is of the form…

Information Theory · Computer Science 2021-06-04 Asaf Ferber , Matthew Kwan , Lisa Sauermann

Let $\lambda$ be the second largest eigenvalue in absolute value of a uniform random $d$-regular graph on $n$ vertices. It was famously conjectured by Alon and proved by Friedman that if $d$ is fixed independent of $n$, then…

Probability · Mathematics 2018-02-08 Nicholas A. Cook , Larry Goldstein , Tobias Johnson

Sensitivity conjecture is a longstanding and fundamental open problem in the area of complexity measures of Boolean functions and decision tree complexity. The conjecture postulates that the maximum sensitivity of a Boolean function is…

Computational Complexity · Computer Science 2014-11-14 Andris Ambainis , Mohammad Bavarian , Yihan Gao , Jieming Mao , Xiaoming Sun , Song Zuo

We give an alternative proof of a conjecture of Bollob\'as, Brightwell and Leader, first proved by Peter Allen, stating that the number of boolean functions definable by 2-SAT formulae is $(1+o(1))2^{\binom{n+1}{2}}$. One step in the proof…

Combinatorics · Mathematics 2010-05-18 Liviu Ilinca , Jeff Kahn

Bernstein's theorem (also called Hausdorff--Bernstein--Widder theorem) enables the integral representation of a completely monotonic function. We introduce a finite completely monotonic function, which is a completely monotonic function…

Numerical Analysis · Mathematics 2023-07-25 Yohei M. Koyama

It was conjectured by Alon and proved by Friedman that a random $d$-regular graph has nearly the largest possible spectral gap, more precisely, the largest absolute value of the non-trivial eigenvalues of its adjacency matrix is at most…

Combinatorics · Mathematics 2019-03-07 Charles Bordenave

It is common to model a deterministic response function, such as the output of a computer experiment, as a Gaussian process with a Mat\'ern covariance kernel. The smoothness parameter of a Mat\'ern kernel determines many important…

Statistics Theory · Mathematics 2023-11-28 Toni Karvonen

We consider the spectral radius of a large random matrix $X$ with independent, identically distributed entries. We show that its typical size is given by a precise three-term asymptotics with an optimal error term beyond the radius of the…

Probability · Mathematics 2024-03-05 Giorgio Cipolloni , László Erdős , Yuanyuan Xu

The reach of a submanifold of $\mathbb{R}^N$ is defined as the largest radius of a tubular neighbourhood around the submanifold that avoids self-intersections. While essential in geometric and topological applications, computing the reach…

Numerical Analysis · Mathematics 2025-05-14 Daniel Platt , Raúl Sánchez Galán

The approximate degree of a Boolean function $f \colon \{-1, 1\}^n \rightarrow \{-1, 1\}$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. We introduce a generic method for increasing the…

Computational Complexity · Computer Science 2017-03-20 Mark Bun , Justin Thaler

Consider the problem of packing Hamming balls of a given relative radius subject to the constraint that they cover any point of the ambient Hamming space with multiplicity at most $L$. For odd $L\ge 3$ an asymptotic upper bound on the rate…

Information Theory · Computer Science 2015-12-29 Yury Polyanskiy

We study the following two related problems. The first is to determine to what error an arbitrary zonoid in $\mathbb{R}^{d+1}$ can be approximated in the Hausdorff distance by a sum of $n$ line segments. The second is to determine optimal…

Machine Learning · Statistics 2025-03-25 Jonathan W. Siegel

We consider the non-parametric maximum likelihood estimation in the class of Polya frequency functions of order two, viz. the densities with a concave logarithm. This is a subclass of unimodal densities and fairly rich in general. The NPMLE…

Statistics Theory · Mathematics 2007-08-22 Jayanta Kumar Pal , Michael Woodroofe , Mary Meyer

Let $D_n$ denote the set of monotone Boolean functions with $n$ variables. Elements of $D_n$ can be represented as strings of bits of length $2^n$. Two elements of $D_0$ are represented as 0 and 1 and any element $g\in D_n$, with $n>0$, is…

Combinatorics · Mathematics 2023-10-20 Bartłomiej Pawelski , Andrzej Szepietowski

It was proved by J. Schatz that the covering radius of the second order Reed--Muller code $RM(2, 6)$ is 18 (IEEE Trans Inf Theory 27: 529--530, 1985). However, the covering radius of $RM(2,7)$ has been an open problem for many years. In…

Information Theory · Computer Science 2018-09-14 Qichun Wang

We study Wiener-type covering lemmas, Hardy-Littlewood-type maximal functions, and convergence theorems on metric spacs. Later we specialize down to a result for the Poisson integral. We show that, in a suitably general setting, these three…

Analysis of PDEs · Mathematics 2010-10-08 Steven G. Krantz

We prove that if $f(n)$ is a Steinhaus or Rademacher random multiplicative function, there almost surely exist arbitrarily large values of $x$ for which $|\sum_{n \leq x} f(n)| \geq \sqrt{x} (\log\log x)^{1/4+o(1)}$. This is the first such…

Number Theory · Mathematics 2021-01-01 Adam J. Harper

Submodular function minimization is well studied, and existing algorithms solve it exactly or up to arbitrary accuracy. However, in many applications, such as structured sparse learning or batch Bayesian optimization, the objective function…

Machine Learning · Computer Science 2022-03-10 Marwa El Halabi , Stefanie Jegelka