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The motivation of this work stems from the numerical approximation of bounded functions by polynomials satisfying the same bounds. The present contribution makes use of the recent algebraic characterization found in [B. Despr\'es, Numer.…

Numerical Analysis · Mathematics 2020-06-30 Martin Campos Pinto , Frédérique Charles , Bruno Després , Maxime Herda

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

Polynomial approximations to boolean functions have led to many positive results in computer science. In particular, polynomial approximations to the sign function underly algorithms for agnostically learning halfspaces, as well as…

Computational Complexity · Computer Science 2014-12-09 Mark Bun , Thomas Steinke

We study the approximation capabilities of two families of univariate polynomials that arise in applications of quantum signal processing. Although approximation only in the domain $[0,1]$ is physically desired, these polynomial families…

Classical Analysis and ODEs · Mathematics 2022-04-11 Rahul Sarkar , Theodore J. Yoder

We give new quantum algorithms for evaluating composed functions whose inputs may be shared between bottom-level gates. Let $f$ be an $m$-bit Boolean function and consider an $n$-bit function $F$ obtained by applying $f$ to conjunctions of…

Quantum Physics · Physics 2021-09-22 Mark Bun , Robin Kothari , Justin Thaler

In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closed-form…

Machine Learning · Statistics 2015-06-02 Nicholas G. Polson , James G. Scott , Brandon T. Willard

We introduce a problem class we call Polynomial Constraint Satisfaction Problems, or PCSP. Where the usual CSPs from computer science and optimization have real-valued score functions, and partition functions from physics have monomials,…

Discrete Mathematics · Computer Science 2010-01-14 Alexander D. Scott , Gregory B. Sorkin

We study spectral algorithms for the high-dimensional Nearest Neighbor Search problem (NNS). In particular, we consider a semi-random setting where a dataset $P$ in $\mathbb{R}^d$ is chosen arbitrarily from an unknown subspace of low…

Data Structures and Algorithms · Computer Science 2014-08-05 Amirali Abdullah , Alexandr Andoni , Ravindran Kannan , Robert Krauthgamer

Let $ACC \circ THR$ be the class of constant-depth circuits comprised of AND, OR, and MOD$m$ gates (for some constant $m > 1$), with a bottom layer of gates computing arbitrary linear threshold functions. This class of circuits can be seen…

Computational Complexity · Computer Science 2014-01-13 Ryan Williams

In this paper, p-dispersion problems are studied to select $p\geqslant 2$ representative points from a large 2D Pareto Front (PF), solution of bi-objective optimization. Four standard p-dispersion variants are considered. A novel variant,…

Data Structures and Algorithms · Computer Science 2023-07-04 Nicolas Dupin

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

We introduce the graph parameter boolean-width, related to the number of different unions of neighborhoods across a cut of a graph. Boolean-width is similar to rank-width, which is related to the number of $GF[2]$-sums (1+1=0) of…

Data Structures and Algorithms · Computer Science 2011-03-10 B. -M. Bui-Xuan , J. A. Telle , M. Vatshelle

The polynomial method from circuit complexity has been applied to several fundamental problems and obtains the state-of-the-art running times. As observed in [Alman and Williams, STOC 2017], almost all applications of the polynomial method…

Computational Complexity · Computer Science 2018-11-20 Lijie Chen , Ruosong Wang

In recent years much effort has been concentrated towards achieving polynomial time lower bounds on algorithms for solving various well-known problems. A useful technique for showing such lower bounds is to prove them conditionally based on…

Data Structures and Algorithms · Computer Science 2017-07-26 Isaac Goldstein , Tsvi Kopelowitz , Moshe Lewenstein , Ely Porat

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

The problem of constructing explicit functions which cannot be approximated by low degree polynomials has been extensively studied in computational complexity, motivated by applications in circuit lower bounds, pseudo-randomness,…

Computational Complexity · Computer Science 2014-12-16 Abhishek Bhowmick , Shachar Lovett

This paper presents a novel method for generating a single polynomial approximation that produces correctly rounded results for all inputs of an elementary function for multiple representations. The generated polynomial approximation has…

Mathematical Software · Computer Science 2022-03-18 Mridul Aanjaneya , Jay P. Lim , Santosh Nagarakatte

In analogy with the regularity lemma of Szemer\'edi, regularity lemmas for polynomials shown by Green and Tao (Contrib. Discrete Math. 2009) and by Kaufman and Lovett (FOCS 2008) modify a given collection of polynomials \calF =…

Computational Complexity · Computer Science 2013-11-21 Arnab Bhattacharyya , Pooya Hatami , Madhur Tulsiani

We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem…

Computational Complexity · Computer Science 2013-01-07 Adam Klivans , Raghu Meka

We survey the main results of approximation theory for adaptive piecewise polynomial functions. In such methods, the partition on which the piecewise polynomial approximation is defined is not fixed in advance, but adapted to the given…

Numerical Analysis · Mathematics 2015-03-17 Albert Cohen , Jean-Marie Mirebeau
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