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Course Details

Spring 2017-2018
APC 537 / ELE 537   P/D/F Only

Information Theory and Machine Learning Seminar

Emmanuel A. Abbe

This advanced seminar discusses topics in information theory, coding theory and machine learning. The goal is to cover different approaches driven by both probabilistic and worst-case models, as well as information-theoretic and computational limits. Focus is put on compression and unsupervised learning. The class has lectures and students presentations.


Sample reading list:
See instructor for complete list

Requirements/Grading:
Oral Presentation(s) - 50%
Class/Precept Participation - 50%

Other Requirements:
Open to Graduate Students Only.

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
43199 S01 03:00:00 pm - 04:20:00 pm T Th   Fine Hall   322   Enrolled:6 Limit:15