2013-2026 Publications

• 2026
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, C. Desnuelle, A.‑S. Rolland, D. Devos, P.‑F. Pradat : “Feature selection using metaheuristics to predict annual amyotrophic lateral sclerosis progression.”, Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, vol. 27 (1-2), pp. 62-77, (Taylor & Francis) (2026)
• 2025
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Toward Robust Prediction : An Empirical Study of Feature Selection Methods”, (2025)
  • V. Bouquet, F. Delbot, Ch. Picouleau : “Partition of graphs with maximum degree ratio”, Annals of Operations Research, (Springer Verlag) (2025)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Comparaison expérimentale d’algorithmes d’invalidation automatique de conjectures en théorie des graphes”, (2025)
  • V. Bouquet, F. Delbot, Ch. Picouleau : “Partition of graphs with maximum degree ratio”, (2025)
• 2024
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, P.‑F. Pradat : “Machine Learning and Feature Selection Methods to Predict 1-Year Disease Progression for Amyotrophic Lateral Sclerosis”, (2024)
  • V. Bouquet, F. Delbot, Ch. Picouleau, S. Rovedakis : “On the complexity of Dominating Set for graphs with fixed diameter”, Theoretical Computer Science, vol. 1001, pp. 114561, (Elsevier) (2024)
• 2022
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, P.‑F. Pradat : “Use of metaheuristics for machine learning in the context of ALS”, 8^th ALS and MND research meeting, Paris, France (2022)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Experimental Comparison of Metaheuristics for Feature Selection in Machine Learning in the Medical Context”, Artificial Intelligence Applications and Innovations, vol. AICT-647 (Part II), IFIP Advances in Information and Communication Technology, Hersonissos, Greece, pp. 194-205, (Springer International Publishing), (ISBN: 978-3-031-08336-5) (2022)
  • V. Bouquet, F. Delbot, Ch. Picouleau : “Partition de graphe sous contrainte de ratio de degré”, 23^e congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France (2022)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Comparaison expérimentale de métaheuristiques pour la sélection de variables dans le cadre de l’apprentissage automatique appliqué au domaine médical”, 23^e congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France (2022)
• 2021
  • V. Grollemund, G. Le Chat, M.‑S. Secchi‑Buhour, F. Delbot, J.‑F. Pradat‑Peyre, P. Bede, P.‑F. Pradat : “Manifold learning for amyotrophic lateral sclerosis functional loss assessment”, Journal of Neurology, vol. 268 (3), pp. 825-850, (Springer Verlag) (2021)
  • V. Bouquet, F. Delbot, Ch. Picouleau : “On the vertices belonging to all, some, none minimum dominating set”, Discrete Applied Mathematics, vol. 288, pp. 9-19, (Elsevier) (2021)
• 2020
  • V. Grollemund, G. Chat, M.‑S. Secchi‑Buhour, F. Delbot, J.‑F. Pradat‑Peyre, P. Bede, P.‑F. Pradat : “Development and validation of a 1-year survival prognosis estimation model for Amyotrophic Lateral Sclerosis using manifold learning algorithm UMAP”, Scientific Reports, vol. 10 (1), pp. 13378, (Nature Publishing Group) (2020)
  • V. Grollemund, G. Chat, J.‑F. Pradat‑Peyre, F. Delbot : “Manifold Learning for Innovation Funding: Identification of Potential Funding Recipients”, Artificial Intelligence Applications and Innovations, vol. 583, IFIP Advances in Information and Communication Technology, Neos Marmaras, Greece, pp. 119-127, (Springer International Publishing) (2020)
  • V. Bouquet, F. Delbot, Ch. Picouleau, S. Rovedakis : “On Minimum Dominating Sets in cubic and (claw,H)-free graphs”, (2020)
• 2019
  • V. Bouquet, K. Christophe, F. Delbot, G. Chat, J.‑F. Pradat‑Peyre : “Minimum Dominating Set and Maximum Independent Set for Evaluation of EU Funding Polices in Collaboration Networks”, Operations Research Proceedings 2018, Operations Research Proceedings, Brussels, Belgium, pp. 243-249, (Springer International Publishing) (2019)
  • V. Grollemund, P.‑F. Pradat, G. Querin, F. Delbot, G. Le Chat, J.‑F. Pradat‑Peyre, P. Bede : “Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions”, Frontiers in Neuroscience, vol. 13, pp. 135, (Frontiers) (2019)
• 2016
  • F. Delbot, Ch. Laforest, R. Phan : “Hardness Results and Approximation Algorithms for Discrete Optimization Problems with Conditional and Unconditional Forbidden Vertices”, (2016)
• 2015
  • F. Delbot, Ch. Laforest, R. Phan : “Graphs with Forbidden and Required Vertices”, ALGOTEL 2015 — 17^es Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, Beaune, France (2015)
• 2014
  • F. Delbot, Ch. Laforest, S. Rovedakis : “Self-stabilizing Algorithms for Connected Vertex Cover and Clique Decomposition Problems”, 18^th International Conference on Principles of Distributed Systems, OPODIS 2014, vol. 8878, Lecture Notes in Computer Science, Cortina d’Ampezzo, Italy, pp. 307-322, (Springer) (2014)
• 2013
  • F. Delbot, Ch. Laforest, R. Phan : “New Approximation Algorithms for the Vertex Cover Problem”, 24^th International Workshop, IWOCA 2013, vol. 8288, Lecture Notes in Computer Science, Rouen, France, pp. 438-442, (Springer Berlin Heidelberg) (2013)