fasta: Fast Adaptive Shrinkage/Thresholding Algorithm
A collection of acceleration schemes for proximal gradient methods for estimating penalized regression parameters described in
Goldstein, Studer, and Baraniuk (2016) <doi:10.48550/arXiv.1411.3406>. Schemes such as Fast Iterative Shrinkage and Thresholding Algorithm (FISTA) by Beck and Teboulle (2009) <doi:10.1137/080716542>
and the adaptive stepsize rule introduced in Wright, Nowak, and Figueiredo (2009) <doi:10.1109/TSP.2009.2016892> are included. You provide the objective function and proximal mappings, and it takes care of the issues like stepsize selection, acceleration, and stopping conditions for you.
| Version: |
0.1.0 |
| Published: |
2018-04-10 |
| DOI: |
10.32614/CRAN.package.fasta |
| Author: |
Eric C. Chi [aut, cre, trl, cph],
Tom Goldstein [aut] (MATLAB original,
https://www.cs.umd.edu/~tomg/projects/fasta/),
Christoph Studer [aut],
Richard G. Baraniuk [aut] |
| Maintainer: |
Eric C. Chi <ecchi1105 at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Citation: |
fasta citation info |
| CRAN checks: |
fasta results |
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