Christophe Roux

researcher at ZIB since August 2021
doctoral candidate at TUB

📬 Contact

office Room 3107 at ZIB
e-mail roux (at) zib.de
christophe.roux (at) campus.tu-berlin.de
homepage christopheroux.de
languages German, English, and French

🎓 Academic Background

Feb 2018 B.Sc. in Engineering Science at TUB
M.Sc. in Scientific Computing at TUB

🔬 Research

My research interests lie at the intersection of optimization and machine learning. In particular, I am interested in online optimization, federated learning and optimization on riemannian manifolds.

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. MartĂ­nez-Rubio, D., Roux, C., and Pokutta, S. (2024). Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point. [arXiv]
    [BibTeX]
    @misc{mrp_tradeoffs_riemannian_gradient_descent_23,
  archiveprefix = {arXiv},
  eprint = {2403.10429},
  primaryclass = {math.OC},
  year = {2024},
  author = {MartĂ­nez-Rubio, David and Roux, Christophe and Pokutta, Sebastian},
  title = {Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point}
}
  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. MartĂ­nez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2023). Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2023). [arXiv]
    [BibTeX]
    @inproceedings{mrp_accelerated_minmax_riemannian_23,
  year = {2023},
  booktitle = {Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2023)},
  archiveprefix = {arXiv},
  eprint = {2305.16186},
  primaryclass = {math.OC},
  author = {MartĂ­nez-Rubio, David and Roux, Christophe and Criscitiello, Christopher and Pokutta, Sebastian},
  title = {Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties}
}

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}
}

đź’¬ Talks and posters

Conference and workshop talks

Nov 2023
Seminar "Modern Methods in Applied Stochastics and Nonpar..., Berlin
Mar 2023
Optimization and ML Workshop, Waischenfeld

Poster presentations

Mar 2023
Optimization and ML Workshop, Waischenfeld