Ethan Epperly

According to our database, Ethan Epperly authored at least 20 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Does block size matter in randomized block Krylov low-rank approximation?

Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao

CoRR, August, 2025

Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product.

Chris Camaño, Ethan N. Epperly, Joel A. Tropp

CoRR, April, 2025

Stable algorithms for general linear systems by preconditioning the normal equations.

Ethan N. Epperly, Anne Greenbaum, Yuji Nakatsukasa

CoRR, February, 2025

Superfast Direct Inversion of the Nonuniform Discrete Fourier Transform via Hierarchically Semiseparable Least Squares.

Heather Wilber, Ethan N. Epperly, Alex H. Barnett

SIAM J. Sci. Comput., 2025

2024

XTrace: Making the Most of Every Sample in Stochastic Trace Estimation.

Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

SIAM J. Matrix Anal. Appl., March, 2024

Efficient Error and Variance Estimation for Randomized Matrix Computations.

Ethan N. Epperly, Joel A. Tropp

SIAM J. Sci. Comput., February, 2024

Fast and Forward Stable Randomized Algorithms for Linear Least-Squares Problems.

Ethan N. Epperly

SIAM J. Matrix Anal. Appl., 2024

Randomized Kaczmarz with tail averaging.

Ethan N. Epperly, Gil Goldshlager, Robert J. Webber

CoRR, 2024

Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky.

Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

CoRR, 2024

Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers.

Ethan N. Epperly, Maike Meier, Yuji Nakatsukasa

CoRR, 2024

A superfast direct inversion method for the nonuniform discrete Fourier transform.

Heather Wilber, Ethan N. Epperly, Alex H. Barnett

CoRR, 2024

The ESPRIT Algorithm Under High Noise: Optimal Error Scaling and Noisy Super-Resolution.

Zhiyan Ding, Ethan N. Epperly, Lin Lin, Ruizhe Zhang

Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

2023

Robust, randomized preconditioning for kernel ridge regression.

Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber

CoRR, 2023

Kernel Quadrature with Randomly Pivoted Cholesky.

Ethan Epperly, Elvira Moreno

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A Theory of Quantum Subspace Diagonalization.

Ethan N. Epperly, Lin Lin, Yuji Nakatsukasa

SIAM J. Matrix Anal. Appl., September, 2022

$(L_r, L_r, 1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials.

Nithin Govindarajan, Ethan N. Epperly, Lieven De Lathauwer

SIAM J. Matrix Anal. Appl., 2022

Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.

Yifan Chen, Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

CoRR, 2022

Jackknife Variability Estimation For Randomized Matrix Computations.

Ethan N. Epperly, Joel A. Tropp

CoRR, 2022

2021

Minimal Rank Completions for Overlapping Blocks.

Ethan N. Epperly, Nithin Govindarajan, Shivkumar Chandrasekaran

CoRR, 2021

2019

Graph-Induced Rank Structures and their Representations.

Shivkumar Chandrasekaran, Ethan Epperly, Nithin Govindarajan

CoRR, 2019