Christophe Roux

Preprints

1. Roux, C., Zimmer, M., and Pokutta, S. (2024). On the Byzantine-resilience of Distillation-based Federated Learning. [arXiv]
   [BibTeX]

   @misc{byzantinefederated2024,
     archiveprefix = {arXiv},
     eprint = {2402.12265},
     primaryclass = {cs.LG},
     year = {2024},
     author = {Roux, Christophe and Zimmer, Max and Pokutta, Sebastian},
     title = {On the Byzantine-resilience of Distillation-based Federated Learning}
   }

2. Martínez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2023). Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. [arXiv]
   [BibTeX]

   @misc{mrp_accelerated_minmax_riemannian_23,
     archiveprefix = {arXiv},
     eprint = {2305.16186},
     primaryclass = {math.OC},
     year = {2023},
     author = {Martínez-Rubio, David and Roux, Christophe and Criscitiello, Christopher and Pokutta, Sebastian},
     title = {Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties}
   }

3. Roux, C., Wirth, E., Pokutta, S., and Kerdreux, T. (2021). Efficient Online-bandit Strategies for Minimax Learning Problems. [arXiv]
   [BibTeX]

   @misc{online.bandit-minimax_2021,
     archiveprefix = {arXiv},
     eprint = {2105.13939},
     primaryclass = {cs.LG},
     year = {2021},
     author = {Roux, Christophe and Wirth, Elias and Pokutta, Sebastian and Kerdreux, Thomas},
     title = {Efficient Online-bandit Strategies for Minimax Learning Problems}
   }

Conference proceedings

1. Martínez-Rubio, D., Roux, C., and Pokutta, S. (2024). Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point. Proceedings of International Conference on Machine Learning. [arXiv]
   [BibTeX]

   @inproceedings{mrp_tradeoffs_riemannian_gradient_descent_23,
     year = {2024},
     booktitle = {Proceedings of International Conference on Machine Learning},
     archiveprefix = {arXiv},
     eprint = {2403.10429},
     primaryclass = {math.OC},
     author = {Martínez-Rubio, David and Roux, Christophe and Pokutta, Sebastian},
     title = {Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point}
   }

Full articles

1. Kerdreux, T., Roux, C., d’Aspremont, A., and Pokutta, S. (2021). Linear Bandits on Uniformly Convex Sets. Journal of Machine Learning Research, 22(284), 1–23. [URL] [arXiv] [summary]
   [BibTeX]

   @article{KRAP2021,
     year = {2021},
     journal = {Journal of Machine Learning Research},
     month = mar,
     volume = {22},
     number = {284},
     pages = {1–23},
     url = {http://jmlr.org/papers/v22/21-0277.html},
     archiveprefix = {arXiv},
     eprint = {2103.05907},
     primaryclass = {cs.LG},
     author = {Kerdreux, Thomas and Roux, Christophe and d'Aspremont, Alexandre and Pokutta, Sebastian},
     title = {Linear Bandits on Uniformly Convex Sets},
     summary = {https://www.pokutta.com/blog/research/2021/04/03/linearBandits.html}
   }