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A natural measure of smoothness of a Boolean function is its sensitivity (the largest number of Hamming neighbors of a point which differ from it in function value). The structure of smooth or equivalently low-sensitivity functions is still…

Computational Complexity · Computer Science 2015-08-12 Parikshit Gopalan , Noam Nisan , Rocco A. Servedio , Kunal Talwar , Avi Wigderson

The noise sensitivity of a Boolean function $f: \{0,1\}^n \rightarrow \{0,1\}$ is one of its fundamental properties. A function of a positive noise parameter $\delta$, it is denoted as $NS_{\delta}[f]$. Here we study the algorithmic problem…

Data Structures and Algorithms · Computer Science 2019-04-16 Ronitt Rubinfeld , Arsen Vasilyan

The {\em Total Influence} ({\em Average Sensitivity) of a discrete function is one of its fundamental measures. We study the problem of approximating the total influence of a monotone Boolean function \ifnum\plusminus=1 $f: \{\pm1\}^n…

Data Structures and Algorithms · Computer Science 2011-01-28 Dana Ron , Ronitt Rubinfeld , Muli Safra , Omri Weinstein

The spectral norm of a Boolean function $f:\{0,1\}^n \to \{-1,1\}$ is the sum of the absolute values of its Fourier coefficients. This quantity provides useful upper and lower bounds on the complexity of a function in areas such as learning…

Computational Complexity · Computer Science 2012-05-25 Anil Ada , Omar Fawzi , Hamed Hatami

The sensitivity conjecture of Nisan and Szegedy [CC '94] asks whether for any Boolean function $f$, the maximum sensitivity $s(f)$, is polynomially related to its block sensitivity $bs(f)$, and hence to other major complexity measures.…

Computational Complexity · Computer Science 2016-12-08 Karthik C. S. , Sébastien Tavenas

In this paper we construct a cyclically invariant Boolean function whose sensitivity is $\Theta(n^{1/3})$. This result answers two previously published questions. Tur\'an (1984) asked if any Boolean function, invariant under some transitive…

Computational Complexity · Computer Science 2007-05-23 Sourav Chakraborty

The sensitivity of a Boolean function f is the maximum over all inputs x, of the number of sensitive coordinates of x. The well-known sensitivity conjecture of Nisan (see also Nisan and Szegedy) states that every sensitivity-s Boolean…

Computational Complexity · Computer Science 2016-04-27 Parikshit Gopalan , Rocco Servedio , Avishay Tal , Avi Wigderson

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

In this paper we prove results regarding Boolean functions with small spectral norm (the spectral norm of f is $\|\hat{f}\|_1=\sum_{\alpha}|\hat{f}(\alpha)|$). Specifically, we prove the following results for functions $f:\{0,1\}^n \to…

Computational Complexity · Computer Science 2013-05-23 Amir Shpilka , Avishay Tal , Ben lee Volk

Suppose that f is a boolean function from F_2^n to {0,1} with spectral norm (that is the sum of the absolute values of its Fourier coefficients) at most M. We show that f may be expressed as +/- 1 combination of at most 2^(2^(O(M^4)))…

Classical Analysis and ODEs · Mathematics 2010-04-02 Ben Green , Tom Sanders

We prove that, to compute a Boolean function $f$ on $N$ variables with error probability $\epsilon$, any quantum black-box algorithm has to query at least $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

Quantum Physics · Physics 2007-05-23 Yaoyun Shi

We study a natural complexity measure of Boolean functions known as the rational degree. Denoted $\textrm{rdeg}(f)$, it is the minimal degree of a rational function that is equal to $f$ on the Boolean hypercube. For total functions $f$, it…

Computational Complexity · Computer Science 2025-04-16 Vishnu Iyer , Siddhartha Jain , Robin Kothari , Matt Kovacs-Deak , Vinayak M. Kumar , Luke Schaeffer , Daochen Wang , Michael Whitmeyer

We give a non-adaptive algorithm that makes $2^{\tilde{O}(\sqrt{k\log(1/\varepsilon_2 - \varepsilon_1)})}$ queries to a Boolean function $f:\{\pm 1\}^n \rightarrow \{\pm 1\}$ and distinguishes between $f$ being $\varepsilon_1$-close to some…

Data Structures and Algorithms · Computer Science 2024-04-23 Shivam Nadimpalli , Shyamal Patel

Boolean functions with symmetry properties are interesting from a complexity theory perspective; extensive research has shown that these functions, if nonconstant, must have high `complexity' according to various measures. In recent work of…

Computational Complexity · Computer Science 2010-01-14 Andrew Drucker

$\newcommand{\sp}{\mathsf{sparsity}}\newcommand{\s}{\mathsf{s}}\newcommand{\al}{\mathsf{alt}}$ The well-known Sensitivity Conjecture states that for any Boolean function $f$, block sensitivity of $f$ is at most polynomial in sensitivity of…

Computational Complexity · Computer Science 2019-02-12 Krishnamoorthy Dinesh , Jayalal Sarma

A Boolean function $f({\vec x})$ is sensitive to bit $x_i$ if there is at least one input vector $\vec x$ and one bit $x_i$ in $\vec x$, such that changing $x_i$ changes $f$. A function has sensitivity $s$ if among all input vectors, the…

Computational Complexity · Computer Science 2023-06-27 Jon T. Butler , Tsutomu Sasao , Shinobu Nagayama

We show how to compute any symmetric Boolean function on $n$ variables over any field (as well as the integers) with a probabilistic polynomial of degree $O(\sqrt{n \log(1/\epsilon)})$ and error at most $\epsilon$. The degree dependence on…

Data Structures and Algorithms · Computer Science 2016-11-18 Josh Alman , Ryan Williams

Sensitivity, block sensitivity and certificate complexity are basic complexity measures of Boolean functions. The famous sensitivity conjecture claims that sensitivity is polynomially related to block sensitivity. However, it has been…

Computational Complexity · Computer Science 2015-06-09 Andris Ambainis , Krišjānis Prūsis , Jevgēnijs Vihrovs

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

We investigate the relation between the block sensitivity $\text{bs}(f)$ and fractional block sensitivity $\text{fbs}(f)$ complexity measures of Boolean functions. While it is known that $\text{fbs}(f) = O(\text{bs}(f)^2)$, the best known…

Computational Complexity · Computer Science 2018-10-08 Andris Ambainis , Krišjānis Prūsis , Jevgēnijs Vihrovs
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