Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...

For our current edition of “Video Highlights” I’d like to offer this talk that will review a series of recent papers that develop new methods based on machine learning methods to approach problems of ...

The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

Stern, Ariel Dora, and W. Nicholson Price, II. "Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning." Biostatistics 21, no. 2 ...

SAN FRANCISCO--(BUSINESS WIRE)--Today MLCommons™, an open engineering consortium, released new results for three MLPerf™ benchmark suites - Inference v2.0, Mobile v2.0, and Tiny v0.7. These three ...

SAN FRANCISCO – April 6, 2022 – Today MLCommons, an open engineering consortium, released new results for three MLPerf benchmark suites – Inference v2.0, Mobile v2.0, and Tiny v0.7. MLCommons said the ...

The launch of Amazon Elastic Inference lets customers add GPU acceleration to any EC2 instance for faster inference at 75 percent savings. Typically, the average utilization of GPUs during inference ...

The manufacturing landscape is evolving rapidly, with intelligent systems increasingly promising to boost efficiency, quality, and overall competitiveness. Traditional machine learning (ML) has ...

ArthAlpha, a next-generation quantitative investment firm, today announced the official launch of MEQ (Machine Learning Equity Quant), an AI-powered equity quant investment strategy rooted in ...