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Probabilistic Graphical Models
MATH 275
Fall 2016 not offered

Graphical models are used to represent complex, uncertain relationships among several, possibly very many, variables. They are fundamental in many domains of application, including medical diagnosis and prognosis, vision and image processing, robotics, and computational biology. This course will familiarize students with the graph theory and probability theory needed to discuss graphical models. After that, students will investigate exact and approximate statistical inference for graphical models, learning/inference of parameters, and possibly learning of graph structure.
Credit: 1 Gen Ed Area Dept: NSM MATH
Course Format: Lecture / DiscussionGrading Mode: Graded
Level: UGRD Prerequisites: MATH222
Fulfills a Major Requirement for: (COMP)

Last Updated on APR-18-2024
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