CITATION.bib

% general citation for the package
@article{besanccon2022frankwolfe,
  title={FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank--Wolfe Algorithms and Conditional Gradients},
  author={Besan{\c{c}}on, Mathieu and Carderera, Alejandro and Pokutta, Sebastian},
  journal={INFORMS Journal on Computing},
  year={2022},
  publisher={INFORMS}
}

% to use the monotonic step size strategies
@article{carderera2021simple,
  title={Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions},
  author={Carderera, Alejandro and Besan{\c{c}}on, Mathieu and Pokutta, Sebastian},
  journal={Proceedings of Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

% for blended pairwise
@article{tsuji2022pairwise,
  title={Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding},
  author={Tsuji, Kazuma and Tanaka, Ken’ichiro and Pokutta, Sebastian},
  journal={Proceedings of International Conference on Machine Learning},
  pages={21864--21883},
  year={2022},
}

% for the stochastic Frank-Wolfe with momentum
@InProceedings{pmlr-v162-macdonald22a,
  title = 	 {Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings},
  author =       {Macdonald, Jan and Besan{\c{c}}on, Mathieu E. and Pokutta, Sebastian},
  booktitle = 	 {Proceedings of the 39th International Conference on Machine Learning},
  pages = 	 {14699--14716},
  year = 	 {2022},
  editor = 	 {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
  volume = 	 {162},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {17--23 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v162/macdonald22a/macdonald22a.pdf},
  url = 	 {https://proceedings.mlr.press/v162/macdonald22a.html},
}