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A Python library for self-concordant smooth optimization (Python port of SelfConcordantSmoothOptimization.jl)

Project description

pySCSOpt: Self-Concordant Smooth Optimization in Python

This package is a Python port of most parts of the Julia package SelfConcordantSmoothOptimization.jl. It includes:

  • ProxLQNSCORE a limited-memory version of ProxQNSCORE of the Julia package
  • ProxGGNSCORE
  • ProxNSCORE
  • 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}
}

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