Deep Learning with Yacine on MSN

How to implement stochastic gradient descent with momentum in Python

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.
Yahoo

Opera Parallèle's ‘Hello, Star' transforms a picture book into a celestial new opera

When Opera Parallèle was looking for its next commission, Artist Director Nicole Paiement knew it would take a community - and a lot of lead time. Now three years later, that vision is ready for its ...
New Republic

ICE Detains Citizen After Saying She Doesn’t “Look Like” Her Last Name

ICE agents kidnapped a U.S. citizen in Chicago who had just finished working a double shift because she didn’t “look” American to them. Maria Greeley, 44, was on her way home from her job at Beach Bar ...
IEEE

The Powerball Method With Biased Stochastic Gradient Estimation for Large-Scale Learning Systems

Abstract: The Powerball method, via incorporating a power coefficient into conventional optimization algorithms, has been considered in accelerating stochastic optimization (SO) algorithms in recent ...
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 ...
Forbes

Employee Engagement In The Flow Of Work: Why Action Planning Alone Falls Short

Latin American man working at a creative office using his computer and people moving at the background - place of work concepts The employee engagement survey reminder pings in inboxes. Some people ...
JSTOR Daily

Scalable statistical inference for averaged implicit stochastic gradient descent

Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...
IEEE

On the Convergence of (Stochastic) Gradient Descent for Kolmogorov–Arnold Networks

Abstract: Kolmogorov–Arnold Networks (KANs), a recently proposed neural network architecture, have gained significant attention in the deep learning community, due to their potential as a viable ...
Microsoft

Stochastic Gradient Descent Tricks

The first chapter of Neural Networks, Tricks of the Trade strongly advocates the stochastic back-propagation method to train neural networks. This is in fact an instance of a more general technique ...