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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