67 citations · 107 across the 27 of their papers we have counts for
5 papers · 1 filter
Randomized Kaczmarz with tail averaging
Ethan N. Epperly, Gil Goldshlager, Robert J. Webber
The randomized Kaczmarz (RK) method is a well-known approach for solving linear least-squares problems with a large number of rows. RK accesses and processes just one row at a time…
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
Randomly pivoted Cholesky (RPCholesky) is an algorithm for constructing a low-rank approximation of a positive-semidefinite matrix using a small number of columns. This paper devel…
Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers
Ethan N. Epperly, Maike Meier, Yuji Nakatsukasa
One of the greatest success stories of randomized algorithms for linear algebra has been the development of fast, randomized algorithms for highly overdetermined linear least-squar…
Superfast direct inversion of the nonuniform discrete Fourier transform via hierarchically semi-separable least squares
Heather Wilber, Ethan N. Epperly, Alex H. Barnett
A direct solver is introduced for solving overdetermined linear systems involving nonuniform discrete Fourier transform matrices. Such matrices can be transformed into a Cauchy-lik…
The ESPRIT algorithm under high noise: Optimal error scaling and noisy super-resolution
Zhiyan Ding, Ethan N. Epperly, Lin Lin +1
Subspace-based signal processing techniques, such as the Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT) algorithm, are popular methods for spectral es…