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Linear regression using gradient descent explained simply

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 ...
Scientific Research Publishing

Ruder, S. (2016) An Overview of Gradient Descent Optimization Algorithms. arXiv Preprint.

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 ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
IEEE

A Globally Convergent Improved Hybrid Method of Quasi Newton and Conjugate Gradient Method

Abstract: A new algorithm which combines the Quasi-Newton (QN) method and conjugate gradient (CG) method are presented in this paper. It is denoted as $\mathbf{QN}-\mathbf{WAM}+$ method and tested ...
IEEE

Automatic Tuning of Adaptive Gradient Descent Based Motion Cueing Algorithm Using Particle Swarm Optimisation

Abstract: A Motion Cueing Algorithm (MCA) is an algorithm that transforms the movement of a simulated vehicle into movement that can be reproduced with a Motion Simulator (MS) while respecting its ...
insideHPC

RMSprop Optimization Algorithm for Gradient Descent with Neural Networks

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...