Statistical machine learning is at the core of modern-day advances in artificial intelligence, but RIT professor Ernest Fokoué argues that applying it correctly requires equal parts science and art.

On February 24, 1956, Arthur Samuel’s Checkers program, which was developed for play on the IBM 701, ...More was demonstrated to the public on television. IBM ...

Well, first, in this study the machine learning methods outperformed the statistical methods for al evaluation metrics. In particular, the precision values of the ML models were higher, and greater ...

In addition to machine learning, expanded statistical areas include causal inference with the support of conditional average treatment effects (CATEs), panel data with high-dimensional fixed ...

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

We believe that machine learning should come with guarantees. It takes much more than inputs and outputs (or transfer characteristics) to solve the hardest problems. MTRI scientists are active in ...

Students gave their consent that their stories could be used for research purposes and might be published. Out of a class of ...

Government agencies are awash in documents. Some of them, like Bureau Labor Statistics (BLS), turn to machine learning to help improve and streamline various processes.

Machine learning has a wide range of applications in the finance, healthcare, marketing and transportation industries. It is used to analyze and process large amounts of data, make predictions ...