Machine Learning

Description

It is difficult to separate machine learning from artificial intelligence at Brown. Most of the AI faculty utilize statistical machine learning techniques in their work whether they focus on machine vision, robotics, or computational linguistics. Hidden Markov models, stochastic context-free grammars, graphical models (Bayesian networks and Markov random fields), and Markov decision processes are common mathematical tools used in developing new algorithms and applications. There are active reading groups and a good deal of collaboration among faculty in computer science and with colleagues in applied math, cognitive and linguistic sciences, engineering, and neuroscience.