Ethan Epperly

Orcid: 0000-0003-0712-8296

According to our database1, Ethan Epperly authored at least 26 papers between 2019 and 2026.

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Bibliography

2026
Fast, High-Accuracy, Randomized Nullspace Computations for Tall Matrices.
CoRR, February, 2026

Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop.
CoRR, February, 2026

The matrix-vector complexity of Ax=b.
CoRR, February, 2026

Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product.
Quantum, 2026

Does block size matter in randomized block Krylov low-rank approximation?
Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

2025
Make the most of what you have: Resource-efficient randomized algorithms for matrix computations.
CoRR, December, 2025

Adaptive randomized pivoting and volume sampling.
CoRR, October, 2025

Faster Linear Algebra Algorithms with Structured Random Matrices.
CoRR, August, 2025

Stable algorithms for general linear systems by preconditioning the normal equations.
CoRR, February, 2025

Superfast Direct Inversion of the Nonuniform Discrete Fourier Transform via Hierarchically Semiseparable Least Squares.
SIAM J. Sci. Comput., 2025

Embrace Rejection: Kernel Matrix Approximation by Accelerated Randomly Pivoted Cholesky.
SIAM J. Matrix Anal. Appl., 2025

2024
XTrace: Making the Most of Every Sample in Stochastic Trace Estimation.
SIAM J. Matrix Anal. Appl., March, 2024

Efficient Error and Variance Estimation for Randomized Matrix Computations.
SIAM J. Sci. Comput., February, 2024

Fast and Forward Stable Randomized Algorithms for Linear Least-Squares Problems.
SIAM J. Matrix Anal. Appl., 2024

Randomized Kaczmarz with tail averaging.
CoRR, 2024

Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers.
CoRR, 2024

A superfast direct inversion method for the nonuniform discrete Fourier transform.
CoRR, 2024

The ESPRIT Algorithm Under High Noise: Optimal Error Scaling and Noisy Super-Resolution.
Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

2023
Robust, randomized preconditioning for kernel ridge regression.
CoRR, 2023

Kernel Quadrature with Randomly Pivoted Cholesky.
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.
SIAM J. Matrix Anal. Appl., September, 2022

$(L_r, L_r, 1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials.
SIAM J. Matrix Anal. Appl., 2022

Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.
CoRR, 2022

Jackknife Variability Estimation For Randomized Matrix Computations.
CoRR, 2022

2021
Minimal Rank Completions for Overlapping Blocks.
CoRR, 2021

2019
Graph-Induced Rank Structures and their Representations.
CoRR, 2019


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