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Reduced Basis Methods: From Low-Rank Matrices to Low-Rank Tensors., and . SIAM J. Sci. Comput., (2016)Krylov Subspace Methods for Linear Systems with Tensor Product Structure., and . SIAM J. Matrix Anal. Appl., 31 (4): 1688-1714 (2010)Low-rank updates and divide-and-conquer methods for quadratic matrix equations., , and . Numer. Algorithms, 84 (2): 717-741 (2020)Fast Computation of the Matrix Exponential for a Toeplitz Matrix., and . SIAM J. Matrix Anal. Appl., 39 (1): 23-47 (2018)Norm and Trace Estimation with Random Rank-one Vectors., and . SIAM J. Matrix Anal. Appl., 42 (1): 202-223 (2021)Structure-Preserving Low Multilinear Rank Approximation of Antisymmetric Tensors., and . SIAM J. Matrix Anal. Appl., 38 (3): 967-983 (2017)Memory-efficient Krylov subspace techniques for solving large-scale Lyapunov equations.. CACSD, page 613-618. IEEE, (2008)On the Curvature of Pattern Transformation Manifolds: Numerical Estimation and Applications., , and . AAAI Fall Symposium: Manifold Learning and Its Applications, volume FS-10-06 of AAAI Technical Report, AAAI, (2010)Truncated low-rank methods for solving general linear matrix equations., and . Numerical Lin. Alg. with Applic., 22 (3): 564-583 (2015)On Randomized Trace Estimates for Indefinite Matrices with an Application to Determinants., and . Found. Comput. Math., 22 (3): 875-903 (2022)