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Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems
Yuji Nakatsukasa, Joel A. Tropp
This paper develops a new class of algorithms for general linear systems and eigenvalue problems. These algorithms apply fast randomized sketching to accelerate subspace projection…
Randomized Nyström Preconditioning
Zachary Frangella, Joel A. Tropp, Madeleine Udell
This paper introduces the Nyström PCG algorithm for solving a symmetric positive-definite linear system. The algorithm applies the randomized Nyström method to form a low-rank appr…
Randomized block Krylov methods for approximating extreme eigenvalues
Joel A. Tropp
Randomized block Krylov subspace methods form a powerful class of algorithms for computing the extreme eigenvalues of a symmetric matrix or the extreme singular values of a general…
Tensor Random Projection for Low Memory Dimension Reduction
Yiming Sun, Yang Guo, Joel A. Tropp +1
Random projections reduce the dimension of a set of vectors while preserving structural information, such as distances between vectors in the set. This paper proposes a novel use o…