ADELPHI, Md.-- Army researchers discovered a way to quickly get information to Soldiers in combat using new machine learning techniques. The algorithms will play a significant role in enhancing ...

Training a machine learning algorithm to accurately solve complex problems requires large amounts of data. Previous articles in this series discussed an exascale-capable machine learning algorithm and ...

These algorithms have evolved from early theoretical constructs into practical solutions that underpin modern cloud infrastructures, the Internet of Things (IoT) and even machine learning deployments.

Algorithms are implemented with different parallelism strategies, ... MLlib: A Natively Distributed Machine Learning Framework. The Apache Spark distributed computing framework, used throughout ...

Traditional machine learning algorithms, dataframe operations like groupby-aggregations, joins, and timeseries manipulation. Data ingestion like CSV and JSON parsing. And array computing like ...

The newly-open sourced Distributed Machine Learning Toolkit features fast, parallelized, and easy-to-deploy machine learning algorithms Topics Spotlight: AI-ready data centers ...

That’s why Amini focuses on algorithms for individualized learning and decision-making within the larger infrastructure. His recent paper on distributed sensing platforms for distributed machine ...