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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 9:04AM Monday, November 28, 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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