Physics of foam strangely resembles AI training

Foams are everywhere: soap suds, shaving cream, whipped toppings and food emulsions like mayonnaise. For decades, scientists ...
Learn With Jay on MSN

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 ...
Scientific Research Publishing

Vanishing Gradients in an Artificial Deep Neural Network: The Impact of Activation ...

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 the ...
Hacker

Why Gradient Descent Converges (and Sometimes Doesn’t) in Neural Networks

Amplifying words and ideas to separate the ordinary from the extraordinary, making the mundane majestic. Amplifying words and ideas to separate the ordinary from the ...
Frontiers

VIO-GO: optimizing event-based SLAM parameters for robust performance in high dynamic range ...

This paper addresses a critical challenge in Industry 4.0 robotics by enhancing Visual Inertial Odometry (VIO) systems to operate effectively in dynamic and low-light industrial environments, which ...
IEEE

An Improved Adagrad Gradient Descent Optimization Algorithm

Abstract: Gradient descent optimization algorithm is very important in deep learning. In order to obtain a more stable convergence process and reduce overfitting in multiple epochs, we propose an ...