Tech Xplore

A novel deep learning architecture for multi-source data fusion

Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two ...
Devdiscourse

Quantum machine learning shows promise for adaptive learning, but classrooms are not ready

Read more about Quantum machine learning shows promise for adaptive learning, but classrooms are not ready on Devdiscourse ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using JavaScript

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...
C&EN

A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

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 ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

Find out how this structured machine learning roadmap called I-Con could lead to breakthroughs in AI. A new “periodic table for machine learning” is reshaping how researchers explore AI, unlocking ...
IEEE

Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks

Abstract: Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical ...
IEEE

Multi-Kernel Learning for Heterogeneous Data

Abstract: Multi-kernel learning is an excellent machine learning algorithm widely used in various learning tasks such as classification and regression. Traditional kernel methods mainly focus on ...