Node-based optimization of LoRa transmissions with Multi-Armed Bandit algorithms R Kerkouche, R Alami, R Féraud, N Varsier, P Maillé 2018 25th International Conference on Telecommunications (ICT), 521-526, 2018 | 48 | 2018 |
Reinforcement learning techniques for optimized channel hopping in IEEE 802.15. 4-TSCH networks H Dakdouk, E Tarazona, R Alami, R Féraud, GZ Papadopoulos, P Maillé Proceedings of the 21st ACM International Conference on Modeling, Analysis …, 2018 | 38 | 2018 |
Toward an uncertainty principle for weighted graphs B Pasdeloup, R Alami, V Gripon, M Rabbat 2015 23rd European Signal Processing Conference (EUSIPCO), 1496-1500, 2015 | 34 | 2015 |
Decentralized exploration in multi-armed bandits R Féraud, R Alami, R Laroche International Conference on Machine Learning, 1901-1909, 2019 | 26 | 2019 |
Restarted Bayesian online change-point detector achieves optimal detection delay R Alami, O Maillard, R Féraud International conference on machine learning, 211-221, 2020 | 25 | 2020 |
Memory Bandits: A Bayesian approach for the Switching Bandit problem R Alami, O Maillard, R Feraud Advances in Neural Information Processing Systems (NIPS): Bayesian …, 2017 | 23 | 2017 |
pymgrid: An open-source python microgrid simulator for applied artificial intelligence research G Henri, T Levent, A Halev, R Alami, P Cordier arXiv preprint arXiv:2011.08004, 2020 | 15 | 2020 |
Uncertainty principle on graphs B Pasdeloup, V Gripon, R Alami, MG Rabbat Vertex-Frequency Analysis of Graph Signals, 317-340, 2019 | 15 | 2019 |
Memory Bandits: Towards the Switching Bandit Problem Best Resolution R Alami, OA Maillard, R Féraud MLSS 2018-Machine Learning Summer School, 2018 | 5 | 2018 |
Distributional deep Q-learning with CVaR regression M Achab, R Alami, YAD Djilali, K Fedyanin, E Moulines, M Panov Deep Reinforcement Learning Workshop NeurIPS 2022, 2022 | 3 | 2022 |
Supervised Feature Space Reduction for Multi-Label Nearest Neighbors W Siblini, R Alami, F Meyer, P Kuntz IEA/AIE 2017: 30th International Conference on Industrial Engineering and …, 2017 | 3 | 2017 |
Bayesian change-point detection for bandit feedback in non-stationary environments R Alami Asian Conference on Machine Learning, 17-31, 2023 | 2 | 2023 |
Ts-glr: an adaptive thompson sampling for the switching multi-armed bandit problem R Alami, O Azizi NeurIPS 2020 challenges of real world reinforcement learning workshop, 2020 | 2 | 2020 |
Toward An Uncertainty Principle For Weighted Graphs P Bastien, A Réda, G Vincent, R Michael Signal Processing Conference (EUSIPCO), 1511-1515, 2015 | 2 | 2015 |
Emergent Communication in Multi-Agent Reinforcement Learning for Future Wireless Networks M Chafii, S Naoumi, R Alami, E Almazrouei, M Bennis, M Debbah IEEE Internet of Things Magazine 6 (4), 18-24, 2023 | 1 | 2023 |
SOREO: a system for safe and autonomous drones fleet navigation with reinforcement learning R Alami, H Hacid, L Bellone, M Barcis, E Natalizio Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 16398 …, 2023 | 1 | 2023 |
One-Step Distributional Reinforcement Learning M Achab, R Alami, YAD Djilali, K Fedyanin, E Moulines arXiv preprint arXiv:2304.14421, 2023 | 1 | 2023 |
Graph Signal Processing: Towards The Diffused Spectral Clustering R Alami | 1 | 2019 |
Non-Stationary Thompson Sampling For Stochastic Bandits with Graph-Structured Feedback R Alami | 1 | 2019 |
Thompson Sampling for the non-Stationary Corrupt Multi-Armed Bandit R Alami The 14th European Workshop on Reinforcement Learning 14, 2018 | 1 | 2018 |