Probabilistic Graphical Models and Structured Prediction


CS6424.  Advanced concepts in machine learning.  Probabilistic graphical modesl and structured output prediction.  Directed models (Bayes Nets), undirected models (Markov/Conditional Random Fields), exact inference (junction tree), approximate inference (belief propagation, dual decomposition), parameter learning (MLE, MAP, EM, max-margin), structure learning.  Cross-listed with ECE 6424. (3H, 3C)

Prerequisites: CS 5824 or ECE 5424

Taught By: Bert Huang