% Key papers for Projection-free conditional gradient (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2018_a_36469,
  title = {{A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2152},
}

@inproceedings{icml2017_conditional_36104,
  title = {{Conditional Accelerated Lazy Stochastic Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/510},
}

@inproceedings{icml2018_projection_36937,
  title = {{Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2385},
}

@inproceedings{neurips2016_faster_55733,
  title = {{Faster Projection-free Convex Optimization over the Spectrahedron}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7078},
}

@inproceedings{icml2019_blended_37195,
  title = {{Blended Conditonal Gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4183},
}

@inproceedings{icml2018_non_36875,
  title = {{Non-convex Conditional Gradient Sliding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1947},
}

@inproceedings{icml2017_a_36036,
  title = {{A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/511},
}

@inproceedings{icml2019_a_37093,
  title = {{A Conditional-Gradient-Based Augmented Lagrangian Framework}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4129},
}

@inproceedings{icml2016_efficient_35813,
  title = {{Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/yao16.html},
}

@inproceedings{neurips2018_limited_57339,
  title = {{Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11436},
}

@inproceedings{icml2020_conditional_38033,
  title = {{Conditional gradient methods for stochastically constrained convex minimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5974},
}

@inproceedings{icml2021_parameter_39774,
  title = {{Parameter-free Locally Accelerated Conditional Gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9511},
}

@inproceedings{neurips2020_efficient_59773,
  title = {{Efficient Projection-free Algorithms for Saddle Point Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16919},
}

@inproceedings{icml2021_one_39725,
  title = {{One-sided Frank-Wolfe algorithms for saddle problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8533},
}

@inproceedings{icml2022_pairwise_40990,
  title = {{Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17205},
}

@inproceedings{icml2024_projection_43370,
  title = {{Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35082},
}

@inproceedings{icml2026_on_52385,
  title = {{On Densest \$k\$-Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=VQt4w3lElX},
}

@inproceedings{icml2026_riemannian_54242,
  title = {{Riemannian Dueling Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=nDfDnsyllY},
}

@inproceedings{neurips2020_walking_61083,
  title = {{Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17957},
}

@inproceedings{neurips2021_reusing_61496,
  title = {{Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/25963},
}

@inproceedings{neurips2025_generalized_79630,
  title = {{Generalized Gradient Norm Clipping \& Non-Euclidean \$(L\_0,L\_1)\$-Smoothness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rMdf8jhLR7},
}