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Given a small random sample of $n$-bit strings labeled by an unknown Boolean function, which properties of this function can be tested computationally efficiently? We show an equivalence between properties that are efficiently testable from…

Computational Complexity · Computer Science 2026-04-07 Cynthia Dwork , Pranay Tankala

We study the polynomial approximation of symmetric multivariate functions and of multi-set functions. Specifically, we consider $f(x_1, \dots, x_N)$, where $x_i \in \mathbb{R}^d$, and $f$ is invariant under permutations of its $N$…

Numerical Analysis · Mathematics 2023-02-06 Markus Bachmayr , Geneviève Dusson , Christoph Ortner , Jack Thomas

The absolute separation of a polynomial is the minimum nonzero difference between the absolute values of its roots. In the case of polynomials with integer coefficients, it can be bounded from below in terms of the degree and the height…

Classical Analysis and ODEs · Mathematics 2024-12-10 Yann Bugeaud , Andrej Dujella , Wenjie Fang , Tomislav Pejković , Bruno Salvy

We establish a generic form of hardness amplification for the approximability of constant-depth Boolean circuits by polynomials. Specifically, we show that if a Boolean circuit cannot be pointwise approximated by low-degree polynomials to…

Computational Complexity · Computer Science 2014-04-29 Mark Bun , Justin Thaler

We revisit the problem of learning mixtures of spherical Gaussians. Given samples from mixture $\frac{1}{k}\sum_{j=1}^{k}\mathcal{N}(\mu_j, I_d)$, the goal is to estimate the means $\mu_1, \mu_2, \ldots, \mu_k \in \mathbb{R}^d$ up to a…

Machine Learning · Computer Science 2022-10-07 Mingda Qiao , Guru Guruganesh , Ankit Singh Rawat , Avinava Dubey , Manzil Zaheer

We prove that the Fourier dimension of any Boolean function with Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof method yields an improved bound of $\widetilde{O}(\sqrt{s})$ assuming a conjecture of…

Computational Complexity · Computer Science 2014-07-15 Swagato Sanyal

The probabilistic degree of a Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ is defined to be the smallest $d$ such that there is a random polynomial $\mathbf{P}$ of degree at most $d$ that agrees with $f$ at each point with high…

Computational Complexity · Computer Science 2019-10-08 Srikanth Srinivasan , Utkarsh Tripathi , S. Venkitesh

We consider the Stochastic Boolean Function Evaluation (SBFE) problem in the well-studied case of $k$-of-$n$ functions: There are independent Boolean random variables $x_1,\dots,x_n$ where each variable $i$ has a known probability $p_i$ of…

Data Structures and Algorithms · Computer Science 2025-11-25 Mads Anker Nielsen , Lars Rohwedder , Kevin Schewior

We provide asymptotically sharp bounds for the Gaussian surface area and the Gaussian noise sensitivity of polynomial threshold functions. In particular we show that if $f$ is a degree-$d$ polynomial threshold function, then its Gaussian…

Computational Complexity · Computer Science 2009-12-15 Daniel M. Kane

Let f(x) = f(x_1, ..., x_n) = \sum_{|S| <= k} a_S \prod_{i \in S} x_i be an n-variate real multilinear polynomial of degree at most k, where S \subseteq [n] = {1, 2, ..., n}. For its "one-block decoupled" version, f~(y,z) = \sum_{|S| <= k}…

Discrete Mathematics · Computer Science 2015-12-08 Ryan O'Donnell , Yu Zhao

In a recent work with Kindler and Wimmer we proved an invariance principle for the slice for low-influence, low-degree functions. Here we provide an alternative proof for general low-degree functions, with no constraints on the influences.…

Probability · Mathematics 2019-01-29 Yuval Filmus , Elchanan Mossel

Let $f$ and $g$ be Boolean functions over a finite Abelian group $\mathcal{G}$, where $g$ is fully known, and we have {\em query access} to $f$, that is, given any $x \in \mathcal{G}$ we can get the value $f(x)$. We study the tolerant…

Computational Complexity · Computer Science 2025-07-11 Swarnalipa Datta , Arijit Ghosh , Chandrima Kayal , Manaswi Paraashar , Manmatha Roy

Advances in neural architecture search, as well as explainability and interpretability of connectionist architectures, have been reported in the recent literature. However, our understanding of how to design Bayesian Deep Learning (BDL)…

Machine Learning · Computer Science 2021-06-24 Nidhin Harilal , Udit Bhatia , Auroop R. Ganguly

In this note we compare two measures of the complexity of a class $\mathcal F$ of Boolean functions studied in (unconditional) pseudorandomness: $\mathcal F$'s ability to distinguish between biased and uniform coins (the coin problem), and…

Computational Complexity · Computer Science 2020-09-01 Rohit Agrawal

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

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 block bootstrap confidence interval based on dependent data can outperform the computationally more convenient normal approximation only with non-trivial Studentization which, in the case of complicated statistics, calls for highly…

Methodology · Statistics 2008-04-29 Stephen M. S. Lee , P. Y. Lai

$\newcommand{\EC}{\mathsf{EC}}\newcommand{\KW}{\mathsf{KW}}\newcommand{\DT}{\mathsf{DT}}\newcommand{\psens}{\mathsf{psens}} \newcommand{\calB}{{\cal B}} $ For a Boolean function $f:\{0,1\}^n \to \{0,1\}$ computed by a circuit $C$ over a…

Computational Complexity · Computer Science 2020-09-17 Krishnamoorthy Dinesh , Samir Otiv , Jayalal Sarma

We study sharp detection thresholds for degree corrections in Stochastic Block Models in the context of a goodness of fit problem, and explore the effect of the unknown community assignment (a high dimensional nuisance parameter) and the…

Statistics Theory · Mathematics 2019-07-16 Rajarshi Mukherjee , Subhabrata Sen

In this paper, we develop a new deflation technique for refining or verifying the isolated singular zeros of polynomial systems. Starting from a polynomial system with an isolated singular zero, by computing the derivatives of the input…

Symbolic Computation · Computer Science 2019-01-01 Jin-San Cheng , Xiaojie Dou , Junyi Wen
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