Foams are everywhere: soap suds, shaving cream, whipped toppings and food emulsions like mayonnaise. For decades, scientists ...

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 ...

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 ...

This valuable study uses state-of-the-art neural encoding and video reconstruction methods to achieve a substantial improvement in video reconstruction quality from mouse neural data. It provides a ...

What comes after Transformers? Google Research is proposing a new way to give sequence models usable long term memory with Titans and MIRAS, while keeping training parallel and inference close to ...

For years, SEOs optimized pages around keywords. But Google now understands meaning through entities and how they relate to one another: people, products, concepts, and their topical connections ...

1 College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, China 2 Xinjiang Key Laboratory of Water Engineering Safety and Water Disaster Prevention, Urumqi, ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

Abstract: In this article, we explore the use of gradient-based optimization algorithms for automated bias control in Mach–Zehnder modulators (MZMs). We present and demonstrate, experimentally, five ...

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 ...