/RPCholesky.jl

Randomly Pivoted Cholesky algorithm, implemented in Julia

Primary LanguageJupyter NotebookMIT LicenseMIT

RPCholesky.jl

Randomly Pivoted Cholesky algorithm, implemented in Julia, based on the description in https://arxiv.org/abs/2207.06503 by Chen et al.

Getting RPCholesky.jl

This package has been added to General Registry. You can install it with the command:

(@v1.x) pkg> add RPCholesky

TO DO

  • Implement blocked RPCholesky
  • Implement RPCholesky accelerated spectral clustering

About

This package has been developed in conjunction with R.J. Webber and D. Aristoff.

This work has been supported by:

  • NSF DMS-2111278

References

  • Y. Chen, E. N. Epperly, J. A. Tropp, and R. J. Webber, “Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.” arXiv, Feb. 22, 2023. doi: 10.48550/arXiv.2207.06503.
  • M. Díaz, E. N. Epperly, Z. Frangella, J. A. Tropp, and R. J. Webber, “Robust, randomized preconditioning for kernel ridge regression.” arXiv, Aug. 02, 2023. doi: 10.48550/arXiv.2304.12465.