Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...

Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...

Abstract: We introduce, for the first time in wireless communication networks, a quantum gradient descent (QGD) algorithm to maximize sum data rates in non-orthogonal multiple access (NOMA)-based ...

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...