Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

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 ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

WEST LAFAYETTE, Ind. — To expand the availability of electricity generated from nuclear power, several countries have started developing designs for small modular reactors (SMRs), which could take ...

In the rapidly evolving landscape of data science and machine learning, ensuring accessibility of data is critical for obtaining meaningful insights. Continuous data plays a pivotal role in various ...

Technological Advancements: Continuous advancements in sensor technology, big data analytics, and machine learning algorithms have fueled the growth of the predictive maintenance market. These ...

Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...

Three new books warn against turning into the person the algorithm thinks you are. Like a lot of Netflix subscribers, I find that my personal feed tends to be hit or miss. Usually more miss. The ...