A new study provides a rigorous theoretical and numerical analysis of the accuracy of the method of characteristics (MoC), a ...

Keywords 👉 Learn how to evaluate the integral of a function. The integral, also called antiderivative, of a function, is the ...

Keywords 👉 Learn how to evaluate the integral of a function. The integral, also called antiderivative, of a function, is the ...

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 ...

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 ...

Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values ...

Robotic surfaces consisting of many actuators can change shape to perform tasks, such as object transportation and sorting. Increasing the number of actuators can enhance the robot’s capacity, but ...

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 ...

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 ...