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 Functions and Optimization Techniques ()

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 ...
Frontiers

A total organic carbon prediction algorithm for heterogeneous shale based on interpretable neural network: a case study of Qiongzhusi Formation shale in the Sichuan Basin

Total Organic Carbon (TOC) is a fundamental parameter for evaluating source rock quality, yet the strong heterogeneity of the Qiongzhusi Formation shale reservoir in the Sichuan Basin severely limits ...
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 ...
Frontiers

Horizontal federated learning and assessment of Cox models

1 Applied Cryptography & Quantum Applications, Netherlands Institute for Applied Scientific Research (TNO), The Hague, Netherlands 2 Data Science, Netherlands Institute for Applied Scientific Research ...
IEEE

DMCN Nash Seeking Based on Distributed Approximate Gradient Descent Optimization Algorithms for MASs

Abstract: A key problem in multiagent multitask systems is optimizing conflict-free strategies, especially when task-assignment is coupled with path-planning. Incomplete information exacerbates this ...