Publications

Here are a list of my published articles, technical reports, and preprints in chronological order. In most of my published work, authors are listed alphabetically. Papers which do not follow this convention are marked with a †.

  1. E. N. Epperly, G. Goldshlager, & R. J. Webber (2024). Randomized Kaczmarz with tail averaging. arXiv preprint arXiv:2411.19877 [math.NA].
  2. Y. Chen, E. N. Epperly, J. A. Tropp, & R. J. Webber (2024). Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations. Communications on Pure and Applied Mathematics, accepted. (preprint)
  3. E. N. Epperly, J. A. Tropp, & R. J. Webber (2024). Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky. arXiv preprint arXiv:2410.03969 [math.NA].
  4. E. N. Epperly (2024). Fast and forward stable randomized algorithms for linear least-squares problems. SIAM Journal on Matrix Analysis and Applications. (preprint)
  5. Z. Ding, E. N. Epperly, L. Lin, & R. Zhang (2024). The ESPRIT algorithm under high noise: Optimal error scaling and noisy super-resolution. Foundations of Computer Science 2024, accepted. (preprint)
  6. E. N. Epperly, M. Meier, & Y. Nakatsukasa (2024). Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers. arXiv preprint arXiv:2406.03468 [math.NA].
  7. H. Wilber, E. N. Epperly, & A. H. Barnett (2024). A superfast direct inversion method for the nonuniform discrete Fourier transform. arXiv preprint arXiv:2404.13223 [math.NA]. †
  8. E. N. Epperly & J. A. Tropp (2024). Efficient error and variance estimation for randomized matrix computations. SIAM Journal on Scientific Computing. (preprint)
  9. E. N. Epperly, J. A. Tropp, & R. J. Webber (2024). XTrace: Making the most of every sample in stochastic trace estimation. SIAM Journal on Matrix Analysis and Applications. (preprint)
  10. E. N. Epperly & E. Moreno (2023). Kernel quadrature with randomly pivoted Cholesky. NeurIPS 2023, spotlight. (preprint) 
  11. M. Díaz, E. N. Epperly, Z. Frangella, J. A. Tropp, & R. J. Webber (2023). Robust, randomized preconditioning for kernel ridge regression. arXiv preprint arXiv:2304.12465 [math.NA].
  12. E. N. Epperly, L. Lin, & Y. Nakatsukasa (2022). A theory of quantum subspace diagonalization. SIAM Journal on Matrix Analysis and Applications. (preprint)
  13. N. Govindarajan, E. N. Epperly, & L. De Lathauwer (2022). (L_r,L_r,1)-decompositions, sparse component analysis, and the blind separation of sums of exponentials. SIAM Journal on Matrix Analysis and Applications. (preprint) †
  14. E. N. Epperly, N. Govindarajan, & S. Chandrasekaran (2021). Minimal rank completions for overlapping blocks. Linear Algebra and its Applications. (preprint) †
  15. E. N. Epperly, A. T. Barker, & R. D. Falgout (2020). Smoothers for matrix-free algebraic multigrid preconditioning of high-order finite elements. LLNL Technical Report. †
  16. E. N. Epperly & R. B. Sills (2020). Transient solute drag and strain aging of dislocations. Acta Materialia. †
  17. E. N. Epperly & R. B. Sills (2020). Comparison of continuum and cross-core theories of dynamic strain aging. Journal of the Mechanics and Physics of Solids, 103944. †
  18. S. Chandrasekaran, E. N. Epperly, & N. Govindarajan (2019). Graph-induced rank structures and their representations. arXiv preprint arXiv:1911.05858 [math.NA].
  19. Ward, D. K., Zhou, X., Karnesky, R. A., Kolasinski, R., Foster, M. E., Thurmer, K., Chao, P., Epperly, E. N., Zimmerman, J. A., Wong, B. M., & Sills, R. B. (2015). Understanding H isotope adsorption and absorption of Al-alloys using modeling and experiments. Sandia Technical Report. †