New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

The healthcare sector is increasingly reliant on digital technologies, demonstrating a strong commitment to using advanced tools for better patient care and more efficient data management. However, ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

Global climate models capture many of the processes that shape Earth's weather and climate. Based on physics, chemistry, ...

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...