Côme Fiegel

According to our database, Côme Fiegel authored at least 7 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Optimal last-iterate convergence in matrix games with bandit feedback using the log-barrier.

Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Michal Valko, Vianney Perchet

CoRR, April, 2026

Learning to Allocate Resources with Censored Feedback.

Giovanni Montanari, Côme Fiegel, Corentin Pla, Aadirupa Saha, Vianney Perchet

CoRR, February, 2026

2025

The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback.

Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Michal Valko, Vianney Perchet

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Local and Adaptive Mirror Descents in Extensive-Form Games.

Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Nash Learning from Human Feedback.

Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Côme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Adapting to game trees in zero-sum imperfect information games.

Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko

Proceedings of the International Conference on Machine Learning, 2023

2020

Adaptive multi-fidelity optimization with fast learning rates.

Côme Fiegel, Victor Gabillon, Michal Valko

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020