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 ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

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

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 ...

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, ...

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

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 ...

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 ...

When it comes to teaching math, a debate has persisted for decades: How, and to what degree, should algorithms be a focus of learning math? The step-by-step procedures are among the most debated ...