Metadata-Version: 2.1
Name: genosolver
Version: 0.1.0.2
Summary: GENO is a solver for non-linear optimization problems. It can solve constrained and unconstrained problems.
Home-page: http://www.geno-project.org
Author: Soeren Laue
Author-email: soeren.laue@uni-jena.de
License: AGPL-3.0
Project-URL: Source, https://github.com/slaue/genosolver/
Description: # The GENO solver
        
        [![Build Status](https://app.travis-ci.com/slaue/genosolver.svg?token=6e4Ji9xEp8uDra4uHsxu&branch=main)](https://travis-ci.com/slaue/genosolver)
        
        GENO is a solver for non-linear optimization problems. It can solve constrained and unconstrained problems. It is fully written in Python with no dependencies and it can run on the CPU and on the GPU.
        
        ## Installing
        
        ```
        pip install genosolver
        ```
        
        ## Project Homepage
        
        See [geno-project.org](http://www.geno-project.org) for more details, examples, and for an easy-to-read  modeling language interface.
        
        
        ## Authors
        
        * [**Sören Laue**](https://theinf2.informatik.uni-jena.de/People/Soeren+Laue.html) - most of the solver -
        * [**Mark Blacher**](https://theinf2.informatik.uni-jena.de/People/Mark+Blacher.html) - GPU support
        * [**Matthias Mitterreiter**](https://theinf2.informatik.uni-jena.de/People/Matthias+Mitterreiter.html)
        
        
        ## License
        
        This project is licensed under the GNU Affero General Public License v3.
        
        ## Papers
        
        For more information, see the papers 
        * [Optimization for Classical Machine Learning Problems on the GPU](https://aaai.org/Conferences/AAAI-22). Sören Laue, Mark Blacher, and Joachim Giesen. In *AAAI Conference on Artificial Intelligence (AAAI),* 2022.
        * [GENO -- GENeric Optimization for Classical Machine Learning](http://papers.nips.cc/paper/8491-geno-generic-optimization-for-classical-machine-learning). Sören Laue, Matthias Mitterreiter, and Joachim Giesen. In *Advances in Neural Information Processing Systems (NeurIPS),* 2019.
        
Keywords: optimization,machine_learning
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
