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math.NA2023
Algorithm-agnostic low-rank approximation of operator monotone matrix functions
David Persson, Raphael A. Meyer, Christopher Musco
Low-rank approximation of a matrix function, , is an important task in computational mathematics. Most methods require direct access to , which is often considerably mo…
cs.DS2023
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation
Raphael A. Meyer, Cameron Musco, Christopher Musco
Krylov subspace methods are a ubiquitous tool for computing near-optimal rank approximations of large matrices. While "large block" Krylov methods with block size at least …