2022

Towards optimal algorithms for multi-player bandits without collision sensing information

Huang, Combes, Trinh
COLT 2022: 35th Conference on Learning Theory, London, Royaume-Uni, 2022

2021

On the Suboptimality of Thompson Sampling in High Dimensions

Zhang, Combes
35th Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual Conference, France, 2021

Statistically Efficient, Polynomial-Time Algorithms for Combinatorial Semi-Bandits

Cuvelier, Combes, Gourdin
SIGMETRICS 2021, Virtual Event, Chine, 2021

Asymptotically Optimal Strategies for Combinatorial Semi-Bandits in Polynomial Time

Cuvelier, Combes, Gourdin
Algorithmic Learning Theory, Paris, France, 2021

2020

Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling

Trinh, Kaufmann, Vernade, Combes
ALT 2020 – 31st International Conference on Algorithmic Learning Theory, San Diego, États-Unis, 2020

2019

Optimal Retransmission Policies for Ultra-Reliable Low Latency Communications with Delayed Feedback

Combes, Elayoubi, Varela
GLOBECOM 2019 – 2019 IEEE Global Communications Conference, Waikoloa, États-Unis, 2019

2018

Device-to-Device Aided Multicasting

Santana, Combes, Kobayashi
2018 IEEE International Symposium on Information Theory (ISIT), Vail, États-Unis, 2018

Approximate ML Detection for MIMO Phase Noise Channels

Combes, Yang
The International Zurich Seminar on Information and Communication, Zurich, Suisse, 2018

2017

Opportunistic Content Delivery in Fading Broadcast Channels

Ghorbel, Ngo, Combes, Kobayashi, Yang
GLOBECOM 2017 – 2017 IEEE Global Communications Conference, Singapore, Singapour, 2017

Minimal Exploration in Structured Stochastic Bandits

Combes, Magureanu, Proutiere
31st Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, États-Unis, 2017

Publications