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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.


Spring 2022 Electrical Engineering E6876 section 001
Sparse and Low-Dimensional Models for Hi
SPARSE MODELS FOR HI-D DA

Call Number 13582
Day & Time
Location
M 1:10pm-3:40pm
750 Schapiro [SCEP]
Points 3
Grading Mode Standard
Approvals Required None
Instructor John Wright
Type LECTURE
Method of Instruction In-Person
Course Description Overview of theory, computation and applications for sparse and low-dimensional data modeling. Recoverability of sparse and low-rank models. Optimization methods for low-dim data modeling. Applications to imaging, neuroscience, communications, web data.
Web Site Vergil
Department Electrical Engineering
Enrollment 37 students (80 max) as of 3:13PM Friday, May 20, 2022
Subject Electrical Engineering
Number E6876
Section 001
Division School of Engineering and Applied Science: Graduate
Open To Columbia College, Engineering:Undergraduate, Engineering:Graduate, GSAS, General Studies
Campus Morningside
Section key 20221ELEN6876E001

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SIS update 05/20/22 15:13    web update 05/20/22 15:33