Abstract: A fast gradient-descent (FGD) method is proposed for far-field pattern synthesis of large antenna arrays. Compared with conventional gradient-descent (GD) methods for pattern synthesis where ...

Abstract: Recently, modified noisy gradient descent bit flipping (MNGDBF) algorithms have been proposed to eliminate the Gaussian random generators required in the original noisy gradient descent bit ...

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...

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 ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

The Alaska Republican senator has no qualms about criticizing the president. She could play a make-or-break role in pushing back on the legislation carrying his agenda. By Catie Edmondson Catie ...

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent ...