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

Supervised learning algorithms extract general principles from observed examples guided by a specific prediction objective.

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...

What is machine learning? Karen Hao Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about.

What it takes to get useful health data from your smartwatch Training an algorithm is an essential part of translating our bodies’ signals into early diagnoses.

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 ...

He’s credited with coming up with the first support vector machine (SVM) algorithm. SVMs are widely used today for machine learning purposes.

The Department of Industrial Engineering and Management Sciences is a leader in the science of decision-making in complex environments through innovation in algorithms, computation, and mathematical ...

Global solar radiation (Hg) is a foundational input for calculating evapotranspiration, crop growth, irrigation needs, and ...