Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Embodied learning for object-centric robotic manipulation is a rapidly developing and challenging area in embodied AI. It is ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

The same type of machine learning methods used to pilot self-driving cars and beat top chess players could help type-1 diabetes sufferers keep their blood glucose levels in a safe range. Scientists at ...

SAN DIEGO, Nov. 18, 2025 /PRNewswire/ -- AI and Machine Learning Unpacked: A Practical Guide for Decision Makers in Life Sciences and Healthcare by Corina J. Shtir, PhD, is now available on Amazon ...

Recent years have seen a significant increase in the availability of large datasets for agriculture applications. Remote ...

According to IEEE, the award “recognizes outstanding original papers published in IEEE/ACM Transactions on Networking or the IEEE Transactions on Network and Service Management” within the last three ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent ...

A NIMS research team has developed a new experimental method capable of rapidly evaluating numerous material compositions by ...

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 ...