How much of machine learning is computer science vs. statistics? originally appeared ... Statisticians are concerned with abstract probability models and don't like to think about how they are ...

For humans and machines, intelligence requires making sense of the world — inferring simple explanations for the mishmosh of information coming in through our senses, discovering regularities and ...

Probability theory provides a framework for modelling uncertainty. I highlight five areas of current research at the frontier of probabilistic machine learning, emphasizing areas that are of broad ...

Many methods from statistics and machine learning (ML) may ... achieved through the creation and fitting of a project-specific probability model. The model allows us to compute a quantitative ...

Most modern learning theory starts with Bayes’ representation of knowledge from probability. In the 1970s, Andrei Kolmogorov put forth a different approach to statistics that coined Kolmogorov ...

Three years later, in 1959, Samuel published “Some Studies in Machine Learning Using the Game of ... of symbols rather than computational statistics as the better path to creating a human ...

Last, but not least, both statistical and machine learning ... of Probability, 26. ISSN 1083-6489. Griffin, Jim E. and Mitrodima, Gelly (2020). A Bayesian quantile time series model for asset returns.

The course provides a precise and accurate treatment of probability ... statistics for the social sciences. Students have the opportunity to engage with some of the most rapidly developing topics ...