The Lancet

Reducing futile donation after circulatory death procurement with machine learning

Donation after circulatory death (DCD) procurements provide an opportunity to alleviate the limited organ supply for solid ...

Stepwise regression predicts Arctic sea-ice extent with high accuracy

Under the influence of global warming, the Arctic is transitioning from a state dominated by multi-year thick ice to a "New ...
devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

In a new comparative analysis of artificial intelligence applications in retail, researchers have revealed that advanced deep learning models can dramatically enhance the accuracy of demand ...
Business Insider

WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025 (GLOBE NEWSWIRE) -- BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology ...
IEEE

Enhancing Accuracy in Sign Language Recognition Using Linear Regression Algorithm with Gradientdescent Over K Nearest Neighbors Algorithm

Abstract: Sign language recognition is an essential task in closing the communication gap between hearing-impaired people and the rest of the population. This paper suggests a better machine learning ...
IEEE

Low-Complexity Inverse Matrix Mini-Batch Gradient Descent for MIMO Equalization and Precoding

Abstract: As the size of base station antenna arrays continues to grow, even with linear processing algorithms, the computational complexity and power consumption required for massive MIMO ...
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 ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...
Wall Street Journal

It’s Known as ‘The List’—and It’s a Secret File of AI Geniuses

All over Silicon Valley, the brightest minds in AI are buzzing about “The List,” a compilation of the most talented engineers and researchers in artificial intelligence that Mark Zuckerberg has spent ...
Frontiers

Distributed quantile regression over sensor networks via the primal–dual hybrid gradient algorithm

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...
Hosted on MSN

Logistic Regression Explained with Gradient Descent — Full Derivation Made Easy!

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...