11 citations · 15 across the 3 of their papers we have counts for
3 papers · 2 filters
An overview of block Gram-Schmidt methods and their stability properties
Erin Carson, Kathryn Lund, Miroslav Rozložník +1
Block Gram-Schmidt algorithms serve as essential kernels in many scientific computing applications, but for many commonly used variants, a rigorous treatment of their stability pro…
Compress-and-restart block Krylov subspace methods for Sylvester matrix equations
Daniel Kressner, Kathryn Lund, Stefano Massei +1
Block Krylov subspace methods (KSMs) comprise building blocks in many state-of-the-art solvers for large-scale matrix equations as they arise, e.g., from the discretization of part…
Limited-memory polynomial methods for large-scale matrix functions
Stefan Güttel, Daniel Kressner, Kathryn Lund
Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various li…