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 ...

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 ...

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More When you look at a baseball player hitting the ball, you can make ...

The Cyber Defense Review, Vol. 6, No. 4, Responding to Proxy Cyber Operations Under International Law (FALL 2021), pp. 95-115 (21 pages) In the field of Artificial Intelligence (AI), Machine Learning ...

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

With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

Panasonic had 14 patents in big data during Q4 2023. Panasonic Holdings Corp filed patents in Q4 2023 for a system using statistical background subtraction to generate causal inference machine ...

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