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 ...

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

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.

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

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 ...

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

By 2014, Facebook had a machine learning algorithm, DeepFace, that could match images of faces to a person with over 97% accuracy, which approaches the performance of a typical human when it comes ...

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...