activity
20232026
most citedRTSMS: Randomized Tucker with single-mode sketching

1 citations · 1 across the 11 of their papers we have counts for

collaborators

17 papers

math.NA2026

Nyström method for symmetric indefinite matrices

Yijia Chen, Yuji Nakatsukasa, Anjali Narendran +1

The Nyström method approximates , where is a column subset ma…

math.NA2026

A multilevel sketch-and-solve method for overdetermined least squares problems

Irina-Beatrice Haas, Michael B. Giles, Yuji Nakatsukasa

Sketch-and-solve (SAS) is a very successful method to efficiently estimate the solution of heavily overdetermined large linear least squares problems. It uses random sketching to r…

math.NA2026

Finding accurate eigenvalues and eigenvectors of positive semi-definite matrices given a subspace

Yuji Nakatsukasa, Zheng Tang

We revisit a classical problem in numerical linear algebra: given an -dimensional subspace that approximates the leading eigenspace of an positive semi…

math.NA2026

Matrix Perturbation Theory in the Tangent Space of Isospectral Matrices

Francesco Hrobat, Yuji Nakatsukasa

Eigenvalue and eigenvector perturbation theory is a fundamental topic in several disciplines, including numerical linear algebra, quantum physics, and related fields. The central p…

math.NA2026

Fast, High-Accuracy, Randomized Nullspace Computations for Tall Matrices

Ethan N. Epperly, Taejun Park, Yuji Nakatsukasa

In this paper, we develop RLOBPCG, an efficient method for computing a small number of singular triplets corresponding to the smallest singular values of large, tall matrices. The…

math.NA2025

Numerical Stability of the Nyström Method

Alberto Bucci, Yuji Nakatsukasa, Taejun Park

The Nyström method is a widely used technique for improving the scalability of kernel-based algorithms, including kernel ridge regression, spectral clustering, and Gaussian process…