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We study the problem of reconstructing a function on a manifold satisfying some mild conditions, given data on the values and some derivatives of the function at arbitrary points on the manifold. While the problem of finding a polynomial of…

Numerical Analysis · Mathematics 2018-05-09 S. Chandrasekaran , C. H. Gorman , H. N. Mhaskar

If $f$ is a nonzero Bohr almost periodic function on $\mathbb R$ with a bounded spectrum we prove there exist $C_f > 0$ and integer $n > 0$ such that for every $u > 0$ the mean measure of the set $\{\, x \, : \, |f(x)| < u \, \}$ is less…

Functional Analysis · Mathematics 2019-04-23 Wayne Lawton

We introduce two forms of correlations on two $d$-level (qudit) systems for entanglement detection. The correlations can be measured via experimentally tractable two local measurement settings and their separable bounds are determined by…

Quantum Physics · Physics 2012-06-07 Ryo Namiki , Yuuki Tokunaga

A theorem is proved concerning approximation of analytic functions by multivariate polynomials in the $s$-dimensional hypercube. The geometric convergence rate is determined not by the usual notion of degree of a multivariate polynomial,…

Numerical Analysis · Mathematics 2016-08-09 Lloyd N. Trefethen

A median-radius framework for assessing centrality in multivariate data using median distances is proposed. Based on the proposed framework, a scale invariant measure of radial dispersion is defined and used to establish a depth function…

Methodology · Statistics 2026-05-14 Elsayed Elamir

We give a complexity dichotomy for the problem of computing the partition function of a weighted Boolean constraint satisfaction problem. Such a problem is parameterized by a set of rational-valued functions, which generalize constraints.…

Computational Complexity · Computer Science 2009-06-03 Andrei Bulatov , Martin Dyer , Leslie Ann Goldberg , Markus Jalsenius , David Richerby

In this paper, exact rate of approximation of functions by linear means of Fourier series and Fourier integrals and corresponding $K$-functionals are expressed via special moduli of smoothness. . Introduction is given in $\S 1$. In $\S2$…

Classical Analysis and ODEs · Mathematics 2016-06-27 R. M. Trigub

Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardness results for the problem of finding a low degree polynomial…

Machine Learning · Computer Science 2010-10-19 Ilias Diakonikolas , Ryan O'Donnell , Rocco A. Servedio , Yi Wu

We study the computational power of polynomial threshold functions, that is, threshold functions of real polynomials over the boolean cube. We provide two new results bounding the computational power of this model. Our first result shows…

Computational Complexity · Computer Science 2009-11-29 Ido Ben-Eliezer , Shachar Lovett , Ariel Yadin

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

The degree of a CSP instance is the maximum number of times that any variable appears in the scopes of constraints. We consider the approximate counting problem for Boolean CSP with bounded-degree instances, for constraint languages…

Computational Complexity · Computer Science 2011-09-19 Martin Dyer , Leslie Ann Goldberg , Markus Jalsenius , David Richerby

The goal of the paper is to relate complexity measures associated with the evaluation of Boolean functions (certificate complexity, decision tree complexity) and learning dimensions used to characterize exact learning (teaching dimension,…

Machine Learning · Computer Science 2012-05-22 Sergiu Goschin

Numerical solutions of differential equations are usually not smooth functions. However, they should resemble the smoothness of the corresponding real solutions in one way or another. In two of our recent papers, a kind of spacial…

Numerical Analysis · Mathematics 2012-07-13 Tong Sun

To determine the dimension of null space of any given linearized polynomial is one of vital problems in finite field theory, with concern to design of modern symmetric cryptosystems. But, the known general theory for this task is much far…

Information Theory · Computer Science 2018-11-29 Sihem Mesnager , Kwang Ho Kim , Myong Song Jo

A simple way to generate a Boolean function is to take the sign of a real polynomial in $n$ variables. Such Boolean functions are called polynomial threshold functions. How many low-degree polynomial threshold functions are there? The…

Probability · Mathematics 2019-07-25 Pierre Baldi , Roman Vershynin

We significantly strengthen and generalize the theorem lifting Nullstellensatz degree to monotone span program size by Pitassi and Robere (2018) so that it works for any gadget with high enough rank, in particular, for useful gadgets such…

Computational Complexity · Computer Science 2020-01-08 Susanna F. de Rezende , Or Meir , Jakob Nordström , Toniann Pitassi , Robert Robere , Marc Vinyals

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

An open problem that is widely regarded as one of the most important in quantum query complexity is to resolve the quantum query complexity of the k-distinctness function on inputs of size N. While the case of k=2 (also called Element…

Quantum Physics · Physics 2023-03-15 Nikhil S. Mande , Justin Thaler , Shuchen Zhu

This study investigates the problem of learning linear block codes optimized for Belief-Propagation decoders significantly improving performance compared to the state-of-the-art. Our previous research is extended with an enhanced system…

Signal Processing · Electrical Eng. & Systems 2025-10-02 Louis-Adrien Dufrène , Quentin Lampin , Guillaume Larue

We give two approximation algorithms solving the Stochastic Boolean Function Evaluation (SBFE) problem for symmetric Boolean functions. The first is an $O(\log n)$-approximation algorithm, based on the submodular goal-value approach of…

Data Structures and Algorithms · Computer Science 2022-01-05 Dimitrios Gkenosis , Nathaniel Grammel , Lisa Hellerstein , Devorah Kletenik