Paper by Erik D. Demaine
- Reference:
- Erik D. Demaine, Jayson Lynch, and Jiaying Sun, “An Efficient Reversible Algorithm for Linear Regression”, in Proceedings of the 2021 International Conference on Rebooting Computing (ICRC 2021), Los Alamitos, California, November 30–December 2, 2021, pages 103–108.
- Abstract:
-
This paper presents an efficient reversible algorithm for linear regression,
both with and without ridge regression. Our reversible algorithm matches the
asymptotic time and space complexity of standard irreversible algorithms for
this problem. Needed for this result is the expansion of the analysis of
efficient reversible matrix multiplication to rectangular matrices and matrix
inversion.
- Comments:
- This paper is also available from IEEE Xplore.
- Length:
- The paper is 6 pages.
- Availability:
- The paper is available in PDF (219k).
- See information on file formats.
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Last updated July 23, 2024 by
Erik Demaine.