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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) <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.
Getting started
Browse package contents
Package details |
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| 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@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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