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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

We study sets $V$ in the tridisc that are relatively polynomially convex and have the polynomial extension property. If $V$ is one-dimensional, and is either algebraic, or has polynomially convex projections, we show that it is a retract.…

Complex Variables · Mathematics 2017-11-29 Lukasz Kosinski , John McCarthy

We study spaces $\mathcal{CV}^{k}(\Omega,E)$ of $k$-times continuously partially differentiable functions on an open set $\Omega\subset\mathbb{R}^{d}$ with values in a locally convex Hausdorff space $E$. The space…

Functional Analysis · Mathematics 2020-02-05 Karsten Kruse

Tame functions are a class of nonsmooth, nonconvex functions, which feature in a wide range of applications: functions encountered in the training of deep neural networks with all common activations, value functions of mixed-integer…

Optimization and Control · Mathematics 2024-06-05 Gilles Bareilles , Johannes Aspman , Jiri Nemecek , Jakub Marecek

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

Distance function to a compact set plays a central role in several areas of computational geometry. Methods that rely on it are robust to the perturbations of the data by the Hausdorff noise, but fail in the presence of outliers. The…

Computational Geometry · Computer Science 2011-02-25 Leonidas J. Guibas , Quentin Mérigot , Dmitriy Morozov

Pasting and Reversing operations have been used successfully over the set of integer numbers, simple permutations, rings and recently over a generalized vector product. In this paper, these operations are defined from a natural way to be…

History and Overview · Mathematics 2013-03-19 Primitivo Acosta-Humánez , Adriana Lorena Chuquen , Ángela Mariette Rodríguez

In this work, we introduce new families of nonconforming approximation methods for reconstructing functions on general polygonal meshes. These methods are defined using degrees of freedom based on weighted moments of orthogonal polynomials…

Numerical Analysis · Mathematics 2025-08-12 Francesco Dell'Accio , Allal Guessab , Gradimir V. Milovanović , Federico Nudo

Vector Fitting (VF) is a popular method of constructing rational approximants that provides a least squares fit to frequency response measurements. In an earlier work, we provided an analysis of VF for scalar-valued rational functions and…

Numerical Analysis · Mathematics 2016-10-05 Zlatko Drmac , Serkan Gugercin , Christopher Beattie

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added…

Functional Analysis · Mathematics 2016-08-30 Fredrik Andersson , Marcus Carlsson , Carl Olsson

This paper investigates the approximation properties of deep neural networks with piecewise-polynomial activation functions. We derive the required depth, width, and sparsity of a deep neural network to approximate any H\"{o}lder smooth…

Numerical Analysis · Mathematics 2022-12-06 Denis Belomestny , Alexey Naumov , Nikita Puchkin , Sergey Samsonov

We give explicit polynomial-sized (in $n$ and $k$) semidefinite representations of the hyperbolicity cones associated with the elementary symmetric polynomials of degree $k$ in $n$ variables. These convex cones form a family of…

Optimization and Control · Mathematics 2016-11-17 James Saunderson , Pablo A. Parrilo

The level of a function f on an n-dimensional space encloses a region. The volume of a region between two such levels depends on both levels. Fixing one of them the volume becomes a function of the remaining level. We show that if the…

Classical Analysis and ODEs · Mathematics 2015-05-13 I. Hoveijn

Given any square matrix or a bounded operator $A$ in a Hilbert space such that $p(A)$ is normal (or similar to normal), we construct a Banach algebra, depending on the polynomial $p$, for which a simple functional calculus holds. When the…

Functional Analysis · Mathematics 2015-06-03 Olavi Nevanlinna

Near-vector spaces extend linear algebra tools to non-linear algebraic structures, enabling the study of non-linear problems. However, explicit constructions remain rare. This paper introduces a broad computable family of near-vector…

Rings and Algebras · Mathematics 2025-04-07 L. Boonzaaier , S. Marques , D. Moore

We use tools of additive combinatorics for the study of subvarieties defined by {\it high rank} families of polynomials in high dimensional $\mathbb{F} _q$-vector spaces. In the first, analytic part of the paper we prove a number properties…

Algebraic Geometry · Mathematics 2020-07-20 David Kazhdan , Tamar Ziegler

A fast approximation to the Boys functions (related to the lower incomplete gamma function of half-integer parameter) by a single closed-form analytical expression for all argument values have been developed and tested. Besides the…

Numerical Analysis · Mathematics 2025-07-09 Dimitri N. Laikov

This paper concerns the approximation of smooth, high-dimensional functions from limited samples using polynomials. This task lies at the heart of many applications in computational science and engineering - notably, some of those arising…

Numerical Analysis · Mathematics 2023-11-07 Ben Adcock , Simone Brugiapaglia

A new representation is proposed for functions in a Sobolev space with dominating mixed smoothness on an $N$-dimensional hyperrectangle. In particular, it is shown that these functions can be expressed in terms of their highest-order mixed…

Numerical Analysis · Mathematics 2024-04-30 Declan S. Jagt , Matthew M. Peet

We present algorithms and heuristics to compute the characteristic polynomial of a matrix given its minimal polynomial. The matrix is represented as a black-box, i.e., by a function to compute its matrix-vector product. The methods apply to…

Symbolic Computation · Computer Science 2009-05-18 Jean-Guillaume Dumas , Clément Pernet , B. David Saunders
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