Tech Xplore

New memristor design uses built-in oxygen gradient to bring stability to reinforcement learning

In a recent study published in Nature Communications, researchers created a memristor that uses a built-in oxygen gradient to ...
Hackaday

Training A Transformer With 1970s-era Technology

Although generative language models have found little widespread, profitable adoption outside of putting artists out of work and giving tech companies an easy scapegoat for cutting staff, their ...
Analytics Insight

Machine Learning, Stanford University

Stanford University’s Machine Learning (XCS229) is a 100% online, instructor-led course offered by the Stanford School of ...
IEEE

Multiplicative Stochastic Gradient Descent for fast and robust deep learning training

Abstract: Even recent Deep Learning (DL) architectures are highly sensitive to training hyperparameters, initial weights, and data distributions, making the development of fast and stable optimization ...

CERN eggheads burn AI into silicon to stem data deluge

feature CERN is nothing like today's agentic AI jockeys, who mostly rely on pre-set weights and generic TPUs and GPUs to ...
Hosted on MSN

Mini-batch gradient descent in deep learning explained

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
usace.army.mil

Army establishes new AI, machine learning career path for officers

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...
Hosted on MSN

Linear regression 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 ...
EurekAlert!

Machine learning-guided gradient dual-proton conducting catalytic layers for high temperature proton exchange membrane fuel cells in aviation

High-temperature proton exchange membrane fuel cells (HT-PEMFCs) are highly promising for next-generation aviation, as they can operate above 160 °C and tolerate impurities in the fuel. However, they ...
Scientific Research Publishing

Bengio, Y., Simard, P. and Frasconi, P. (1994) Learning Long-Term Dependencies with Gradient Descent Is Difficult. IEEE Transactions on Neural Networks, 5, 157-166.

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

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 ...