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Let G be a finite abelian group. This paper is concerned with nonnegative functions on G that are sparse with respect to the Fourier basis. We establish combinatorial conditions on subsets S and T of Fourier basis elements under which…

Optimization and Control · Mathematics 2016-11-30 Hamza Fawzi , James Saunderson , Pablo A. Parrilo

An algorithm for computing the nonlinearity of a Boolean function from its algebraic normal form (ANF) is proposed. By generalizing the expression of the weight of a Boolean function in terms of its ANF coefficients, a formulation of the…

Information Theory · Computer Science 2013-05-07 Çağdaş Çalık

In this paper, we construct an algorithm for minimising piecewise smooth functions for which derivative information is not available. The algorithm constructs a pair of quadratic functions, one on each side of the point with smallest known…

Optimization and Control · Mathematics 2020-12-14 Jonathan Grant-Peters , Raphael Hauser

The quantified Boolean formula (QBF) problem is an important decision problem generally viewed as the archetype for PSPACE-completeness. Many problems of central interest in AI are in general not included in NP, e.g., planning, model…

Computational Complexity · Computer Science 2024-05-13 Leif Eriksson , Victor Lagerkvist , George Osipov , Sebastian Ordyniak , Fahad Panolan , Mateusz Rychlicki

Computing explicitly the {\epsilon}-subdifferential of a proper function amounts to computing the level set of a convex function namely the conjugate minus a linear function. The resulting theoretical algorithm is applied to the the class…

Optimization and Control · Mathematics 2017-09-26 Anuj Bajaj , Warren Hare , Yves Lucet

In this paper we consider an aggregation model f: X1 x ... x Xn --> Y for arbitrary sets X1, ..., Xn and a finite distributive lattice Y, factorizable as f(x1, ..., xn) = p(u1(x1), ..., un(xn)), where p is an n-variable lattice polynomial…

Rings and Algebras · Mathematics 2011-10-11 Miguel Couceiro , Tamás Waldhauser

A new algorithm for one-dimensional minimization is described in detail and the results of some tests on practical cases are reported and illustrated. The method requires only punctual computation of the function, and is suitable to be…

Optimization and Control · Mathematics 2017-08-24 Glauco Masotti

The approximate degree of a Boolean function is the minimum degree of real polynomial that approximates it pointwise. For any Boolean function, its approximate degree serves as a lower bound on its quantum query complexity, and generically…

Computational Complexity · Computer Science 2023-05-23 Mark Bun , Nadezhda Voronova

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

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

The covariance function of a Gauss-Markov process evaluated at points $(s,t)$ admits a representation as a product of a function of $\min(s,t)$ and a function of $\max(s,t)$. We call these functions the covariance factors of a Gauss-Markov…

Probability · Mathematics 2025-08-01 Georges Kassis

Algorithms like those for differentiating functional expressions manipulate the syntactic structure of mathematical expressions in a mathematically meaningful way. A formalization of such an algorithm should include a specification of its…

Logic in Computer Science · Computer Science 2013-08-06 William M. Farmer

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

Soft extrapolation refers to the problem of recovering a function from its samples, multiplied by a fast-decaying window and perturbed by an additive noise, over an interval which is potentially larger than the essential support of the…

Numerical Analysis · Mathematics 2018-12-26 Dmitry Batenkov , Laurent Demanet , Hrushikesh N. Mhaskar

A short introduction to quantum error correction is given, and it is shown that zero-dimensional quantum codes can be represented as self-dual additive codes over GF(4) and also as graphs. We show that graphs representing several such codes…

Quantum Physics · Physics 2008-01-09 Lars Eirik Danielsen

We study functional clones, which are sets of non-negative pseudo-Boolean functions (functions $\{0,1\}^k\to\mathbb{R}_{\geq 0}$) closed under (essentially) multiplication, summation and limits. Functional clones naturally form a lattice…

Discrete Mathematics · Computer Science 2018-04-13 Andrei Bulatov , Leslie Ann Goldberg , Mark Jerrum , David Richerby , Stanislav Živný

In this paper, aliasing effects are investigated for random fields defined on the d-dimensional sphere and reconstructed from discrete samples. First, we introduce the concept of an aliasing function on the sphere. The aliasing function…

Statistics Theory · Mathematics 2019-11-27 Claudio Durastanti , Tim Patschkowski

Consider a sparse polynomial in several variables given explicitly as a sum of non-zero terms with coefficients in an effective field. In this paper, we present several algorithms for factoring such polynomials and related tasks (such as…

Symbolic Computation · Computer Science 2025-02-26 Alexander Demin , Joris van der Hoeven

We derandomize G. Valiant's [J. ACM 62 (2015) Art. 13] subquadratic-time algorithm for finding outlier correlations in binary data. Our derandomized algorithm gives deterministic subquadratic scaling essentially for the same parameter range…

Data Structures and Algorithms · Computer Science 2016-11-09 Matti Karppa , Petteri Kaski , Jukka Kohonen , Padraig Ó Catháin

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