- Schedule of Classes - June 25, 2020 7:14PM EDT
- Course Catalog - June 25, 2020 7:15PM EDT
Course information provided by the Courses of Study 2019-2020.
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 Fall.
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
- TRHollister Hall 206
- Jan 21 - May 5, 2020
Instruction Mode: Hybrid - Online & In Person
Limited to grad students only. All others should add themselves to the waitlist. Please go to http://www.cs.cornell.edu/courseinfo/enrollment for updates.
Disabled for this roster.