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New Undergraduate Course Supplement 2022


COSC 89.31 Deep Learning Generalization and Robustness

This course will be an extended version of COSC 78/278 Deep Learning. It is mostly project-based, and it aims to bridge the gap between machine learning course materials and recent developments in machine learning research. The course begins by covering the basics of model training and inference. From there, the course proceeds to discuss various concepts of generalization, different types of robustness issues associated with generalization (e.g., adversarial robustness, out-of-distribution robustness, model poisoning, etc.), and the connections between (robust) generalization to the design of multiple regularization and normalization strategies.

Degree Requirement Attributes

Dist:TAS

The Timetable of Class Meetings contains the most up-to-date information about a course. It includes not only the meeting time and instructor, but also its official distributive and/or world culture designation. This information supersedes any information you may see elsewhere, to include what may appear in this ORC/Catalog or on a department/program website. Note that course attributes may change term to term therefore those in effect are those (only) during the term in which you enroll in the course.