BACKGROUND: Preeclampsia affects approximately 1 in 10 pregnancies, leading to severe complications and long-term health ...

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 ...

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 ...

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 ...

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 ...

Matrix functions, such as the exponential, square root and cosine, play an indispensable role in various fields including quantum mechanics, control theory and numerical solution of differential ...

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: This paper compares the performance of activation function hardware under exponential function approximation techniques. The activation function is a key component of deep neural networks, ...