Maxime Labonne

According to our database, Maxime Labonne authored at least 15 papers between 2018 and 2024.

Collaborative distances:

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

2024

Estimating class separability of text embeddings with persistent homology.

Kostis Gourgoulias, Najah Ghalyan, Maxime Labonne, Yash Satsangi, Sean Moran, Joseph Sabelja

Trans. Mach. Learn. Res., 2024

The path forward for large language models in medicine is open.

Lars Riedemann, Maxime Labonne, Stephen Gilbert

npj Digit. Medicine, 2024

Merging in a Bottle: Differentiable Adaptive Merging (DAM) and the Path from Averaging to Automation.

Thomas Gauthier-Caron, Shamane Siriwardhana, Elliot Stein, Malikeh Ehghaghi, Charles Goddard, Mark McQuade, Jacob Solawetz, Maxime Labonne

CoRR, 2024

2023

An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning.

Najah Ghalyan, Kostis Gourgoulias, Yash Satsangi, Sean Moran, Maxime Labonne, Joseph Sabelja

CoRR, 2023

Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection.

Maxime Labonne, Sean Moran

CoRR, 2023

2022

Dynamic Link Network Emulation and Validation of Execution Datasets.

Erick Petersen, Jorge López, Natalia Kushik, Maxime Labonne, Claude Poletti, Djamal Zeghlache

Proceedings of the Evaluation of Novel Approaches to Software Engineering, 2022

2021

WIP: Short-Term Flow-Based Bandwidth Forecasting using Machine Learning.

Maxime Labonne, Jorge López, Claude Poletti, Jean-Baptiste Munier

Proceedings of the 22nd IEEE International Symposium on a World of Wireless, 2021

Toward Formal Data Set Verification for Building Effective Machine Learning Models.

Jorge López, Maxime Labonne, Claude Poletti

Proceedings of the 13th International Joint Conference on Knowledge Discovery, 2021

2020

Anomaly-based network intrusion detection using machine learning. (Détection d'intrusion réseau par anomalies avec apprentissage automatique).

Maxime Labonne

PhD thesis, 2020

Short-Term Flow-Based Bandwidth Forecasting using Machine Learning.

Maxime Labonne, Jorge López, Claude Poletti, Jean-Baptiste Munier

CoRR, 2020

Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches.

Jorge López, Maxime Labonne, Claude Poletti, Dallal Belabed

Proceedings of the 19th IEEE International Symposium on Network Computing and Applications, 2020

Unsupervised Protocol-based Intrusion Detection for Real-world Networks.

Maxime Labonne, Alexis Olivereau, Baptiste Polvé, Djamal Zeghlache

Proceedings of the International Conference on Computing, Networking and Communications, 2020

Predicting Bandwidth Utilization on Network Links Using Machine Learning.

Maxime Labonne, Charalampos Chatzinakis, Alexis Olivereau

Proceedings of the 2020 European Conference on Networks and Communications, 2020

2019

A Cascade-structured Meta-Specialists Approach for Neural Network-based Intrusion Detection.

Maxime Labonne, Alexis Olivereau, Baptiste Polvé, Djamal Zeghlache

Proceedings of the 16th IEEE Annual Consumer Communications & Networking Conference, 2019

2018

Anomaly Detection in Vehicle-to-Infrastructure Communications.

Michele Russo, Maxime Labonne, Alexis Olivereau, Mohammad Rmayti

Proceedings of the 87th IEEE Vehicular Technology Conference, 2018