引用 CVXPY

如果你在发表论文或工作中使用CVXPY，我们鼓励你引用相应的 JMLR MLOSS 论文 和 JCD 论文。 请使用下面的 BibTeX 条目：

@article{diamond2016cvxpy,
  author  = {Steven Diamond and Stephen Boyd},
  title   = {{CVXPY}: {A} {P}ython-embedded modeling language for convex optimization},
  journal = {Journal of Machine Learning Research},
  year    = {2016},
  volume  = {17},
  number  = {83},
  pages   = {1--5},
}

@article{agrawal2018rewriting,
  author  = {Agrawal, Akshay and Verschueren, Robin and Diamond, Steven and Boyd, Stephen},
  title   = {A rewriting system for convex optimization problems},
  journal = {Journal of Control and Decision},
  year    = {2018},
  volume  = {5},
  number  = {1},
  pages   = {42--60},
}

许多 CVXPY 的功能最初是作为研究项目开发的。这些 功能及其 BibTeX 条目如下所示。

标准几何规划

@article{agrawal2019dgp,
  author  = {Agrawal, Akshay and Diamond, Steven and Boyd, Stephen},
  title   = {Disciplined geometric programming},
  journal = {Optimization Letters},
  publisher = {Springer Berlin Heidelberg},
  year    = {2019},
  volume = {13},
  number = {5},
  pages = {961--976},
}

规范凸规划

@article{agrawal2020dqcp,
    author       = {Agrawal, Akshay and Boyd, Stephen},
    title        = {Disciplined quasiconvex programming},
    journal      = {Optimization Letters},
    publisher = {Springer Berlin Heidelberg},
    year    = {2020},
    note = {To appear}
}

通过凸优化问题求导

@inproceedings{agrawal2019differentiable,
  title={Differentiable convex optimization layers},
  author={Agrawal, Akshay and Amos, Brandon and Barratt, Shane and Boyd, Stephen and Diamond, Steven and Kolter, J. Zico},
  booktitle={Advances in Neural Information Processing Systems},
  pages={9558--9570},
  year={2019},
}

通过对数对数凸程序求导

@article{agrawal2020differentiating,
  title={Differentiating through log-log convex programs},
  author={Agrawal, Akshay and Boyd, Stephen},
  journal={arXiv},
  archivePrefix={arXiv},
  eprint={2004.12553},
  primaryClass={math.OC},
  year={2020},
}