FedPerf: A Practitioners' Guide to Performance of Federated Learning Algorithms. - Ajinkya Mulay; Gaspard Baye; Rakshit Naidu; Santiago González-Toral; Vineeth S; Tushar Semwal; Ayush Manish Agrawal (Preregister@NeurIPS, 2020)

API Security in Large Enterprises: Leveraging Machine Learning for Anomaly Detection. - Gaspard Baye; Fatima Hussain; Alma Oracevic; Rasheed Hussain; S. M. Ahsan Kazmi (ISNCC, 2021)

Short Paper: Static and Microarchitectural ML-Based Approaches For Detecting Spectre Vulnerabilities and Attacks. - Chidera Biringa; Gaspard Baye; Gökhan Kul (HASP@MICRO, 2022)

Covariate Software Vulnerability Discovery Model to Support Cybersecurity Test & Evaluation (Practical Experience Report). - Julia Sorrentino; Priscila Silva; Gaspard Baye; Gökhan Kul; Lance Fiondella (ISSRE, 2022)

Computing on Wheels: A Deep Reinforcement Learning-Based Approach. - S. M. Ahsan Kazmi; Tai Manh Ho; Tuong Tri Nguyen; Muhammad Fahim; Adil Khan 001; Md. Jalil Piran; Gaspard Baye (IEEE Trans. Intell. Transp. Syst., 2022)

Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems. - Gaspard Baye; Priscila Silva; Alexandre Broggi; Lance Fiondella; Nathaniel D. Bastian; Gökhan Kul (NOMS, 2023)

Predicting F1-Scores of Classifiers in Network Intrusion Detection Systems. - Priscila Silva; Gaspard Baye; Alexandre Broggi; Nathaniel D. Bastian; Gökhan Kul; Lance Fiondella (ICCCN, 2024)

varMax: Towards Confidence-Based Zero-Day Attack Recognition. - Gaspard Baye; Priscila Silva; Alexandre Broggi; Nathaniel D. Bastian; Lance Fiondella; Gökhan Kul (MILCOM, 2024)

Cache Sharing in UAV-Enabled Cellular Network: A Deep Reinforcement Learning-Based Approach. - Hamidullah Muslih; S. M. Ahsan Kazmi; Manuel Mazzara; Gaspard Baye (IEEE Access, 2024)