Course Schedule and Catalog

Long Title: GRAPHICAL MODELS

Department: Statistics

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: This course will focus on providing diverse mathematical tools for graduate students from statistical inference and learning; graph theory, signal processing and systems; coding theory and communications, and information theory. We will discuss exact and approximate statistical inference over large number of interacting variables, and develop probablistics and optimization-based computational methods. We will cover hidden Markov models, belief propagation, Monte Carlo sampling algorithms, and variational Bayesian methods. Cross-list: ELEC 633.