Metadata-Version: 2.1
Name: mlopt
Version: 0.0.2
Summary: The Machine Learning Optimizer
Home-page: https://mlopt.org/
Author: Bartolomeo Stellato, Dimitris Bertsimas
Author-email: bartolomeo.stellato@gmail.com
License: Apache License, Version 2.0
Description: # Machine Learning Optimizer
        
        `mlopt` is a package to learn how to solve numerical optimization problems from data. It relies on [cvxpy](https://cvxpy.org) for modeling and [gurobi](https://www.gurobi.com/) for solving the problem offline.
        
        `mlopt` learns how to solve programs using [pytorch](https://pytorch.org/) ([pytorch-lightning](https://github.com/PyTorchLightning/pytorch-lightning)), [xgboost](https://xgboost.readthedocs.io/en/latest/) or [optimaltrees](https://docs.interpretable.ai/stable). The machine learning hyperparameter optimization is performed using [optuna](https://optuna.org/).
        
        Online, `mlopt` only requires to predict the strategy and solve a linear system using [scikit-umfpack](https://github.com/scikit-umfpack/scikit-umfpack).
        
        ## Examples
        
        To see `mlopt` in action, have a look at the notebooks in the [examples/](./examples/) folder.
        
        ## Documentation
        
        Coming soon at [mlopt.org](https://mlopt.org)!
        
        ## Citing
        
        If you use `mlopt` for research, please cite the following papers:
        
        * [The Voice of Optimization](https://arxiv.org/pdf/1812.09991.pdf):
        
          ```
          @article{mlopt,
            author = {{Bertsimas}, D. and {Stellato}, B.},
            title = {The Voice of Optimization},
            journal = {Machine Learning (to appear)},
            year = {2020},
            month = jun,
          }
          ```
        
        * [Online Mixed-Integer Optimization in Milliseconds](https://arxiv.org/pdf/1907.02206.pdf)
        
          ```
          @article{stellato2019a,
            author = {{Bertsimas}, D. and {Stellato}, B.},
            title = {Online Mixed-Integer Optimization in Milliseconds},
            journal = {INFORMS Journal on Computing (major revision)},
            year = {2019},
            month = jul,
          }
          ```
        
        
        ## Projects using mlopt framework
        
        
        * [Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control](https://arxiv.org/pdf/2004.03736.pdf)
        
        
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