Courses of Study 2018-2019 
    
    Aug 20, 2019  
Courses of Study 2018-2019 [ARCHIVED CATALOG]

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CS 6220 - Data-Sparse Matrix Computations


     
Fall. 4 credits. Student option grading.

Prerequisite: CS 4220  or CS 6210 .

Staff.

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.



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