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In this work we develop a novel recursive method for parametrizing the cone of copositive univariate polynomials of any arbitrary degree $d$. This parametrization is surjective, almost injective, and has the easily described domain of…

Optimization and Control · Mathematics 2024-05-10 Hoon Hong , Ezra Nance

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

The task of approximating a function of d variables from its evaluations at a given number of points is ubiquitous in numerical analysis and engineering applications. When d is large, this task is challenged by the so-called curse of…

Numerical Analysis · Mathematics 2016-12-21 Albert Cohen , Giovanni Migliorati

The paper studies binary classification and aims at estimating the underlying regression function which is the conditional expectation of the class labels given the inputs. The regression function is the key component of the Bayes optimal…

Machine Learning · Statistics 2019-03-26 Balázs Csanád Csáji , Ambrus Tamás

The paper investigates the problem of performing correlation analysis when the number of observations is very large. In such a case, it is often necessary to combine the random observations to achieve dimensionality reduction of the…

Information Theory · Computer Science 2020-10-19 Pavel Loskot

New methods for derivation of Bell polynomials of the second kind are presented. The methods are based on an ordinary generating function and its composita. The relation between a composita and a Bell polynomial is demonstrated. Main…

Combinatorics · Mathematics 2011-09-09 Vladimir Kruchinin

Shape restrictions on functional regression coefficients such as non-negativity, monotonicity, convexity or concavity are often available in the form of a prior knowledge or required to maintain a structural consistency in functional…

Methodology · Statistics 2022-09-13 Rahul Ghosal , Sujit Ghosh , Jacek Urbanek , Jennifer A. Schrack , Vadim Zipunnikov

Motivated by the goal of improving the efficiency of small sample design, we propose a novel Bayesian stochastic approximation method to estimate the root of a regression function. The method features adaptive local modelling and…

Methodology · Statistics 2017-05-08 Jin Xu , Cui Xiong , Rongji Mu

We introduce a novel method for bounding high-order multi-dimensional polynomials in finite element approximations. The method involves precomputing optimal piecewise-linear bounding boxes for polynomial basis functions, which can then be…

Numerical Analysis · Mathematics 2025-04-17 Tarik Dzanic , Tzanio Kolev , Ketan Mittal

Functional quadratic regression models postulate a polynomial relationship between a scalar response rather than a linear one. As in functional linear regression, vertical and specially high-leverage outliers may affect the classical…

Methodology · Statistics 2023-05-30 Graciela Boente , Daniela Parada

We study the problem of approximating and learning coverage functions. A function $c: 2^{[n]} \rightarrow \mathbf{R}^{+}$ is a coverage function, if there exists a universe $U$ with non-negative weights $w(u)$ for each $u \in U$ and subsets…

Machine Learning · Computer Science 2014-05-29 Vitaly Feldman , Pravesh Kothari

In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We derive formulas for the uniform approximation…

Numerical Analysis · Mathematics 2013-08-27 Ryan Anderson , Yuliya Babenko , Tetiana Leskevych

The paper gives a full description of the growth of the gradient of a polynomial in two complex variables at infinity near any fiber of the polynomial

Algebraic Geometry · Mathematics 2007-05-23 Jacek Chadzynski , Tadeusz Krasinski

We propose a new variable selection procedure for a functional linear model with multiple scalar responses and multiple functional predictors. This method is based on basis expansions of the involved functional predictors and coefficients…

Statistics Theory · Mathematics 2023-11-03 Alban Mina Mbina , Guy Martial Nkiet

Given the first 20-100 coefficients of a typical generating function of the type that arises in many problems of statistical mechanics or enumerative combinatorics, we show that the method of differential approximants performs surprisingly…

Statistical Mechanics · Physics 2016-10-12 Anthony J Guttmann

In this article, we give an account of some recent irreducibility testing criteria for polynomials having integer coefficients over the field of rational numbers.

Number Theory · Mathematics 2023-10-05 Sanjeev Kumar , Jitender Singh

Improvements in technology lead to increasing availability of large data sets which makes the need for data reduction and informative subsamples ever more important. In this paper we construct $ D $-optimal subsampling designs for…

Statistics Theory · Mathematics 2023-02-28 Torsten Reuter , Rainer Schwabe

In this paper we obtain several extensions to the quaternionic setting of some results concerning the approximation by polynomials of functions continuous on a compact set and holomorphic in its interior. The results include approximation…

Complex Variables · Mathematics 2023-07-19 Sorin G. Gal , Irene Sabadini

In this paper, new relations between the derivatives of the Legendre polynomials are obtained, and by these relations, new upper bounds for the Legendre coefficients of differentiable functions are presented. These upper bounds are sharp…

Numerical Analysis · Mathematics 2022-07-28 M. Hamzehnejad , M. M. Hosseini , A. Salemi

We describe fast algorithms for approximating the connection coefficients between a family of orthogonal polynomials and another family with a polynomially or rationally modified measure. The connection coefficients are computed via…

Numerical Analysis · Mathematics 2024-03-27 Timon S. Gutleb , Sheehan Olver , Richard Mikael Slevinsky