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 ...

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 ...

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...

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 ...