- Schedule of Classes - September 9, 2021 7:14PM EDT
- Course Catalog - September 9, 2021 7:15PM EDT
Course information provided by the Courses of Study 2020-2021.
Matrices and linear systems can be data-sparse in a wide variety of ways, and we can often leverage such underlying structure to perform matrix computations efficiently. This course will discuss several varieties of structured problems and associated algorithms. Example topics include randomized algorithms for numerical linear algebra, Krylov subspace methods, sparse recovery, and assorted matrix factorizations.
When Offered Spring.
Prerequisites/Corequisites Prerequisite: CS 4220 or CS 6210.
Regular Academic Session.
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Class Number & Section Details
- TROnline Meeting
- Feb 8 - May 14, 2021
Instruction Mode: Online
Enrollment limited to graduate & professional students only. All others may add themselves to the waitlist during add/drop. Please go to http://www.cs.cornell.edu/courseinfo/enrollment for updates.
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