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

Hermite polynomials and functions are widely used for scientific and engineering problems. Although it is known that using the scaled Hermite function instead of the standard one can significantly ...

Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network approximation. However, existing ...

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 ...

The decomposition kinetics of four synthetic alkaline earth metal carbonates (MgCO3, CaCO3, SrCO3 and BaCO3) was studied under non-isothermal conditions from thermo-gravimetric measurements as ...

Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function ...

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 ...

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 ...