Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...

Note that the common "logistic regression" machine learning technique is actually a binary classification system in spite of its name. Arguably the most powerful regression technique is a neural ...

Researchers use a machine learning (ML) approach to obtain the EM-aware aging prediction of the power grid (PG) network. They use neural network--based regression as their core ML technique to ...

Artificial intelligence researchers have celebrated a string of successes with neural networks, computer programs that roughly mimic how our brains are organized. But despite rapid progress, neural ...

Brainchip has introduced a new generation of its unique, bio-inspired Akida line of licensable, configurable neural processing IP.

A resistor that works in a similar way to nerve cells in the body could be used to build neural networks for machine learning. Many large machine learning models rely on increasing amounts of ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

The discovery of tools key to machine learning wins the 2024 physics Nobel This year’s laureates did foundational work on artificial neural networks ...

Digital transactions have emerged as a dominant force in today’s global commerce sector, empowering businesses and financial ...

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...