A Russian mathematician has developed a new method for analyzing a class of equations that underpin models in physics and ...

Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This paper explores the use ...

1 Warwick Mathematics Institute, The University of Warwick, Coventry, United Kingdom 2 School of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, China To ...

Abstract: In this paper, a successive radial basis function (RBF) approximation approach is proposed to solve the Hamilton-Jacobi-Isaacs (HJI) partial differential equation (PDE) associated with ...

The method of nested multiplication is commonly used in function evaluation routines to evaluate approximation polynomials. New polynomial evaluation methods have been developed in recent years which ...

Let $P(m, X, N)$ be an $m$-degree polynomial in $X\in\mathbb{R}$ having fixed non-negative integers $m$ and $N$. Essentially, the polynomial $P(m, X, N)$ is a result ...

Abstract: Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-and-error in the environment ...

A new method of scanning lungs is able to show in real time how air moves in and out of the lungs as people take a breath in patients with asthma, chronic obstructive pulmonary disease (COPD), and ...

ABSTRACT: Accurately approximating higher order derivatives is an inherently difficult problem. It is shown that a random variable shape parameter strategy can improve the accuracy of approximating ...