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Related papers: Linear read-once and related Boolean functions

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We give the first non-trivial upper bounds on the average sensitivity and noise sensitivity of polynomial threshold functions. More specifically, for a Boolean function f on n variables equal to the sign of a real, multivariate polynomial…

Computational Complexity · Computer Science 2014-03-28 Prahladh Harsha , Adam Klivans , Raghu Meka

Given a sequence of Boolean functions $(f_n)_{n \geq 1}$, $f_n \colon \{ 0,1 \}^{n} \to \{ 0,1 \}$, and a sequence $(X^{(n)})_{n\geq 1} $ of continuous time $p_n $-biased random walks $ X^{(n)} = (X_t^{(n)})_{t \geq 0}$ on $ \{ 0,1 \}^{n}$,…

Probability · Mathematics 2021-01-05 Malin Palö Forsström

We study the problem of testing if a function depends on a small number of linear directions of its input data. We call a function $f$ a linear $k$-junta if it is completely determined by some $k$-dimensional subspace of the input space. In…

Computational Complexity · Computer Science 2018-11-05 Anindya De , Elchanan Mossel , Joe Neeman

The threshold degree of a Boolean function $f\colon\{0,1\}^n\to\{0,1\}$ is the minimum degree of a real polynomial $p$ that represents $f$ in sign: $\mathrm{sgn}\; p(x)=(-1)^{f(x)}.$ A related notion is sign-rank, defined for a Boolean…

Computational Complexity · Computer Science 2019-01-07 Alexander A. Sherstov , Pei Wu

This paper investigates the learnability of the nonlinearity property of Boolean functions using neural networks. We train encoder style deep neural networks to learn to predict the nonlinearity of Boolean functions from examples of…

Machine Learning · Computer Science 2025-02-04 Sriram Ranga , Nandish Chattopadhyay , Anupam Chattopadhyay

The extremal function $ex(n, P)$ is the maximum possible number of ones in any 0-1 matrix with $n$ rows and $n$ columns that avoids $P$. A 0-1 matrix $P$ is called minimally non-linear if $ex(n, P) = \omega(n)$ but $ex(n, P') = O(n)$ for…

Combinatorics · Mathematics 2020-11-04 Jesse Geneson , Shen-Fu Tsai

Monotone Boolean functions, and the monotone Boolean circuits that compute them, have been intensively studied in complexity theory. In this paper we study the structure of Boolean functions in terms of the minimum number of negations in…

Computational Complexity · Computer Science 2014-10-31 Eric Blais , Clément L. Canonne , Igor C. Oliveira , Rocco A. Servedio , Li-Yang Tan

A statistical functional, such as the mean or the median, is called elicitable if there is a scoring function or loss function such that the correct forecast of the functional is the unique minimizer of the expected score. Such scoring…

Statistics Theory · Mathematics 2016-08-10 Tobias Fissler , Johanna F. Ziegel

An \emph{arithmetic read-once formula} (ROF for short) is a formula (i.e. a tree of computation) in which the operations are $\{+,\times\}$ and such that every input variable labels at most one leaf. We give a simple characterization of…

Discrete Mathematics · Computer Science 2014-08-12 Ilya Volkovich

This paper considers the problem of approximating a Boolean function $f$ using another Boolean function from a specified class. Two classes of approximating functions are considered: $k$-juntas, and linear Boolean functions. The $n$ input…

Information Theory · Computer Science 2019-07-09 Mohsen Heidari , S. Sandeep Pradhan , Ramji Venkataramanan

Multi-index models - functions which only depend on the covariates through a non-linear transformation of their projection on a subspace - are a useful benchmark for investigating feature learning with neural nets. This paper examines the…

Machine Learning · Computer Science 2025-11-13 Emanuele Troiani , Yatin Dandi , Leonardo Defilippis , Lenka Zdeborová , Bruno Loureiro , Florent Krzakala

An arithmetic read-once formula (ROF) is a formula (circuit of fan-out 1) over $+, \times$ where each variable labels at most one leaf. Every multilinear polynomial can be expressed as the sum of ROFs. In this work, we prove, for certain…

Computational Complexity · Computer Science 2015-12-15 Meena Mahajan , Anuj Tawari

In this paper, we show that the set of continuous functions defined on $\mathbb{R}^n$ that approach zero at infinity and attain their maximum at precisely one (and only one) point is $n$-lineable but not $(n+2)$-lineable. This result…

Functional Analysis · Mathematics 2023-12-11 Anderson Barbosa , Gustavo Araújo

We investigate Boolean degree 1 functions for several classical association schemes, including Johnson graphs, Grassmann graphs, graphs from polar spaces, and bilinear forms graphs, as well as some other domains such as multislices (Young…

Combinatorics · Mathematics 2020-10-08 Yuval Filmus , Ferdinand Ihringer

Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotone. Contrary to what one would expect, not all of these…

Neural and Evolutionary Computing · Computer Science 2015-03-17 Benjamin Doerr , Thomas Jansen , Dirk Sudholt , Carola Winzen , Christine Zarges

We classify the Boolean degree $1$ functions of $k$-spaces in a vector space of dimension $n$ (also known as Cameron-Liebler classes) over the field with $q$ elements for $n \geq n_0(k, q)$. This also implies that two-intersecting sets with…

Combinatorics · Mathematics 2024-05-28 Ferdinand Ihringer

We show examples of total Boolean functions that depend on $n$ variables and have spectral sensitivity $\Theta(\sqrt{\log n})$, which is asymptotically minimal. Our main new function combines the Hamming code with the Boolean address…

Computational Complexity · Computer Science 2025-02-21 Krišjānis Prūsis , Jevgēnijs Vihrovs

The 0-1 matrix A contains a 0-1 matrix M if some submatrix of A can be transformed into M by changing some ones to zeroes. If A does not contain M, then A avoids M. Let ex(n,M) be the maximum number of ones in an n x n 0-1 matrix that…

Combinatorics · Mathematics 2014-10-14 Jesse Geneson , Lilly Shen

Valiant's (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold functions and their various subclasses, such as conjunctions…

Machine Learning · Computer Science 2015-03-19 Vitaly Feldman

We consider the non-trivial zeros of the Riemann $\zeta$-function and two classes of $L$-functions; Dirichlet $L$-functions and those based on level one modular forms. We show that there are an infinite number of zeros on the critical line…

Number Theory · Mathematics 2022-05-24 Guilherme França , André LeClair