Princeton University

CITP Lecture: Amanda Coston - Responsible Machine Learning through the Lens of Causal Inference

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 ...
insideHPC

Video Highlights: Machine Learning and Causal Inference

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 Lancet

From data to decision: the future of prehospital intubation in major trauma

The question of whether prehospital emergency anaesthesia and intubation improves survival in patients with major trauma has ...
JSTOR Daily

Commentary: On Two Approaches to Weighting in Causal Inference

Setodji CM, McCaffrey DF, Burgette LF, Almirall D, Griffin BA. The right tool for the job: Choosing between covariate balancing and generalized boosted model propensity scores. Epidemiology. 2017.
insideHPC

MLPerf Results Highlight Advances in Machine Learning Inference Performance and Efficiency

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 ...
San Diego Reader

Rethinking Machine Learning: Stuart Frost Makes the Case for Causal AI in Manufacturing

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

MLPerf Results Show Advances in Machine Learning Inference Performance and Efficiency

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 ...