pySCSOpt: Self-Concordant Smooth Optimization in Python
This package is a Python port of most parts of the Julia package SelfConcordantSmoothOptimization.jl. It includes:
ProxLQNSCOREa limited-memory version of ProxQNSCORE of the Julia packageProxGGNSCOREProxNSCORE- Smoothing and regularization (utility) functions
Installation
Install with pip:
pip install pyscsopt
Usage
See the examples/ directory for a usage example.
For more information on how to set up problems (especially choosing regularizers), see Julia's SelfConcordantSmoothOptimization.jl.
Tests
Run tests with:
pytest pyscsopt/test/
Citation
If you use this package for research, please cite:
@article{adeoye2023self,
title={Self-concordant Smoothing for Large-Scale Convex Composite Optimization},
author={Adeoye, Adeyemi D and Bemporad, Alberto},
journal={arXiv preprint arXiv:2309.01781},
year={2024}
}
1 maintainer
Metadata
1 maintainer
Release files for pyscsopt 0.1.52
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| pyscsopt-0.1.52.tar.gz | 22.9 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyscsopt-0.1.52-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 47.1 kB
Release files / pyscsopt-0.1.52.tar.gz
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| Size | 24.1 kB |
| Tags | Python 3 |
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