| Encrypted traffic classification at line rate in programmable switches with machine learning ATJ Akem, G Fraysse, M Fiore NOMS 2024-2024 IEEE Network Operations and Management Symposium, 1-9, 2024 | 12 | 2024 |
| A mixture of experts regression model for functional response with functional covariates JS Tamo Tchomgui, J Jacques, G Fraysse, V Barriac, S Chretien Statistics and Computing 34 (5), 154, 2024 | 3 | 2024 |
| A resource usage efficient distributed allocation algorithm for 5G Service Function Chains G Fraysse, J Lejeune, J Sopena, P Sens Distributed Applications and Interoperable Systems: 20th IFIP WG 6.1 …, 2020 | 2 | 2020 |
| Functional Linear Regression for the prediction of streaming video QoE JST Tchomgui, V Barriac, G Fraysse, J Jacques, S Chrétien 2024 20th International Conference on Network and Service Management (CNSM), 1-7, 2024 | 1 | 2024 |
| Generating Commit Messages for Configuration Files in 5G Network Deployment Using LLMs Y Beining, S Alassane, F Guillaume, C Sihem 2024 20th International Conference on Network and Service Management (CNSM), 1-7, 2024 | 1 | 2024 |
| Autoscaling Packet Core Network Functions with Deep Reinforcement Learning J Singh, S Verma, Y Matsuo, F Fossati, G Fraysse NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium, 1-6, 2023 | 1 | 2023 |
| Function-on-Function Mixture of Experts Regression Models JST Tchomgui, J Jacques, S Chrétien, G Fraysse, V Barriac 15th International Conference of the ERCIM WG on Computational and …, 2022 | 1 | 2022 |
| Real‐Time Encrypted Traffic Classification in Programmable Networks with P4 and Machine Learning ATJ Akem, G Fraysse, M Fiore International Journal of Network Management 35 (1), e2320, 2025 | | 2025 |
| PenFFR JST TCHOMGUI, J Jacques, G Fraysse, S Chrétien, V Barriac | | 2024 |
| Safe RL for Core Network autoscaling X Long, G Fraysse 2024 20th International Conference on Network and Service Management (CNSM), 1-7, 2024 | | 2024 |
| A mixture of experts regression model for functional response with functional covariates JS Tamo Tchomgui, J Jacques, G Fraysse, V Barriac, S Chretien Statistics and Computing 34 (5), 154, 2024 | | 2024 |
| Penalized Spline Regression for Gaussian Function-on-Function Mixture-of-Experts JST TCHOMGUI, J Jacques, S Chrétien, G Fraysse, V Barriac ENBIS-24 Conference, 2024 | | 2024 |
| A mixture of experts regression model for functional response with functional covariates T JST, J JACQUES, G FRAYSSE, V BARRIAC, S CHRETIEN | | 2024 |
| Function-on-Function Mixture-of-Experts Regression JST TCHOMGUI, J Jacques, S Chrétien, G Fraysse, V Barriac fda-lille: Functional Data Analysis Workshop, 2024 | | 2024 |
| Modèle de mélanges d'experts pour données fonctionnelles JST TCHOMGUI, J Jacques, S Chrétien, G Fraysse, V Barriac 54es Journées de la Statistique de la SFdS, 2023 | | 2023 |
| Integrating state prediction into the Deep Reinforcement Learning for the Autoscaling of Core Network Functions Y Matsuo, J Singh, S Verma, G Fraysse NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium, 1-5, 2023 | | 2023 |
| Prédiction de la Qualité d'Expérience dans les Réseaux Mobiles: Cas de la VoIP JST Tchomgui, J Jacques, S Chrétien, G Fraysse, V Barriac JDS'22 53es journées de la Statistique de la Société Française de …, 2022 | | 2022 |
| Quality of Experience’s Prediction in Mobile Networks: The case of VoIP service JST TCHOMGUI, J Jacques, G Fraysse, V Barriac, S Chrétien spring school «Statlearn: challenging problems in statistical learning», 2022 | | 2022 |
| Distributed resource allocation for virtual networks G Fraysse Sorbonne Université, CNRS, LIP6, Paris, France, 2020 | | 2020 |
| Mapping the allocation of resources for 5G slices to the k-MUTEX with n instances of m resources problem G Fraysse, J Lejeune, J Sopena, P Sens 2018 14th International Conference on Network and Service Management (CNSM …, 2018 | | 2018 |