Gamification of pure exploration for linear bandits R Degenne, P Ménard, X Shang, M Valko 37th International Conference on Machine Learning, 2020 | 89 | 2020 |
Fixed-confidence guarantees for Bayesian best-arm identification X Shang, R de Heide, E Kaufmann, P Ménard, M Valko 23rd International Conference on Artificial Intelligence and Statistics, 2020 | 66 | 2020 |
UCB momentum Q-learning: Correcting the bias without forgetting P Ménard, OD Domingues, X Shang, M Valko 38th International Conference on Machine Learning, 2021 | 42 | 2021 |
General parallel optimization without a metric X Shang, E Kaufmann, M Valko 30th International Conference on Algorithmic Learning Theory, 2019 | 32 | 2019 |
rlberry - A reinforcement learning library for research and education rlberry Team GitHub repository, 2021 | 18* | 2021 |
A simple dynamic bandit algorithm for hyper-parameter tuning X Shang, E Kaufmann, M Valko 6th ICML Workshop on Automated Machine Learning, 2019 | 11 | 2019 |
Adaptive black-box optimization got easier: HCT only needs local smoothness X Shang, E Kaufmann, M Valko 14th European Workshop on Reinforcement Learning, 2018 | 9 | 2018 |
Hierarchical Bandits for Black-Box Optimization and Monte-Carlo Tree Search X Shang Ecole normale supérieure de Cachan (Rennes), 2017 | 4* | 2017 |
Stochastic bandits with vector losses: Minimizing -norm of relative losses X Shang, H Shao, J Qian 15th European Workshop on Reinforcement Learning, 2022 | 2 | 2022 |
Time series clustering D Barbe, A Debant, X Shang https://xuedong.github.io/static/documents/time_series.pdf, 2016 | 2 | 2016 |
Price of safety in linear best arm identification X Shang, I Colin, M Barlier, H Cherkaoui arXiv preprint arXiv:2309.08709, 2023 | 1 | 2023 |
Adaptive Methods for Optimisation in Stochastic Environments X Shang Université de Lille / Inria Lille, SequeL, 2021 | | 2021 |
LinBAI.jl: Gamification of pure exploration for linear bandits X Shang GitHub repository, 2021 | | 2021 |
Reinforcement Learning Summer School N Carrara, OD Domingues, Y Flet-Berliac, E Kaufmann, E Leurent, ... Scientific Event Organization, 2019 | | 2019 |
Simple (dynamic) bandit algorithms for hyper-parameter optimization X Shang, E Kaufmann, M Valko https://xuedong.github.io/static/documents/dttts.pdf, 2019 | | 2019 |
Optimal transport geometry for sentiment analysis X Shang Yamamoto-Cuturi Lab., Graduate School of Informatics, Kyoto University, 2016 | | 2016 |
Recommandation personnalisée X Shang Team Magnet, Inria Lille - Nord Europe, 2015 | | 2015 |