Rice University statistician Genevera Allen issued a grave warning at a prominent scientific conference this week: that scientists are leaning on machine learning algorithms to find patterns in data ...

Machine learning is everywhere in science and technology: powering facial recognition, picking your recommendations on Netflix, and controlling self-driving cars. But how reliable are machine learning ...

Impactful research meets innovative educational programs in Statistics and Data Sciences, the college’s newest and fastest-growing department. Using novel statistics and machine learning methods to ...

Physicists use theoretical models to study physical quantities, such as the mass of nuclei, where they do not have experimental data. However, using a single imperfect theoretical model can lead to ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Solve Real-World Problems With Applied Statistics. Applied Statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in several fields, ...

Overview: Machine learning failures usually start before modeling, with poor data understanding and preparation.Clean data, ...

John Storey, Princeton University's William R. Harman '63 and Mary-Love Harman Professor in Genomics and professor in the Lewis-Sigler Institute for Integrative Genomics, has received the 2015 COPSS ...

Deep learning is rapidly ‘eating’ artificial intelligence. But let's not mistake this ascendant form of artificial intelligence for anything more than it really is. The famous author Arthur C. Clarke ...