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Contains my Computational Complexity course work at MIPT

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Maximal cut SDP relaxation

This project contains my implementation of SDP relaxation of Max Cut problem, the Goemans-Williamson algorithm, brute force solution, tests for it and the pdf-report about all the work done.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   ├── models         <- Contains maxcut implementations
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── cut_visual.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org

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