Presentation to the New England Artificial Intelligence Group, Cambridge, MA (September 2013)
Probabilistic models form the foundation of modern machine learning (ML) and artificial intelligence (AI). However, building and reasoning on models that represent large and complex scenarios is a daunting task for even the most expert and experienced programmers. As a result, there has been significant effort lately on the development of probabilistic programming languages, which allow probabilistic processes, models, and algorithms to be specified using familiar programming language constructs. These languages are democratizing the AI field, enabling users with little ML and AI experience to easily construct and perform inference on large and complex probabilistic models. This talk discusses the motivation for the advent of probabilistic programming languages and details some of the major problems they are trying to solve, as well as presenting many examples using Figaro, a free, open-source, probabilistic programming language.
For More Information
(Please include your name, address, organization, and the paper reference. Requests without this information will not be honored.)