Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...

Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Smart health refers to the integration of cutting-edge technologies into healthcare systems to improve patient care and apply intelligent clinical decision-making. The study investigates how ...

WASHINGTON, Oct 16 (Reuters) - The chair of the House Select Committee on China said Thursday that a licensing agreement for use of the TikTok algorithm, as part of a deal by China-based ByteDance to ...

The complete copyright-free-for-all approach that OpenAI took to its new AI video generation model, Sora 2, lasted all of one week. After initially requiring copyright holders to opt out of having ...

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning. Putin derides European leaders as he insists Russia's war goals in Ukraine will be met ...

Magnesium oil spray may potentially help with pain relief and improved joint function. However, more research is necessary to support and understand the extent of these potential benefits. Magnesium ...

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 ...

Taylor worked with AP from 2018 to 2025, most recently as Google Editor. Android has offered a system-wide dark theme since 2019's Android 10 release, but historically, it's been opt-in for individual ...

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 ...