<p>Lecture, four hours; discussion, two hours; outside study, six hours. Introduction to computational models of probability and statistical models of relational data. Study of relational representations such as probabilistic databases, relational graphical models, and Markov logic networks, as well as various probabilistic programming languages. Covers their syntax and semantics, probabilistic inference problems, parameter, and structure learning algorithms, and theoretical properties of representation and inference. Expressive statistical modeling, how to formalize and reason about complex statistical assumptions and encode knowledge in machine learning models. Survey of key applications in natural language processing, graph mining, computer vision, and computational biology. Letter grading.</p>

Computer Science

Known as the birthplace of the Internet and where countless other cutting-edge technologies took their first steps, the school is consistently ranked among the top 10 public engineering schools in the U.S.

Henry Samueli School of Engineering and Applied Science

Computer science is concerned with the design, modeling, analysis, and applications of computer systems.

General Catalog

Probabilistic Programming and Relational Learning

COM SCI 267A

4 units