Modelling, Computation and Optimization in Information Systems and Management Sciences | Proceedings of the 5th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2025, Volume 2 | ISBN 9783032083838

Modelling, Computation and Optimization in Information Systems and Management Sciences

Proceedings of the 5th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2025, Volume 2

herausgegeben von Hoai An Le Thi, Tao Pham Dinh und Hoai Minh Le
Mitwirkende
Herausgegeben vonHoai An Le Thi
Herausgegeben vonTao Pham Dinh
Herausgegeben vonHoai Minh Le
Buchcover Modelling, Computation and Optimization in Information Systems and Management Sciences  | EAN 9783032083838 | ISBN 3-032-08383-4 | ISBN 978-3-032-08383-8

Modelling, Computation and Optimization in Information Systems and Management Sciences

Proceedings of the 5th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2025, Volume 2

herausgegeben von Hoai An Le Thi, Tao Pham Dinh und Hoai Minh Le
Mitwirkende
Herausgegeben vonHoai An Le Thi
Herausgegeben vonTao Pham Dinh
Herausgegeben vonHoai Minh Le

This 2-volume set of proceedings contains 62 selected full papers presented at the Fifth International Conference on Modeling, Computation and Optimization in Information Systems and Management Science (MCO 2025), held on June 4–6, 2025, in Metz, France, celebrating the 40th anniversary of DC (Difference of Convex functions) programming and DCA (DC Algorithms)—pioneering and highly influential methodologies founded by Pham Dinh Tao and Le Thi Hoai An.
This second volume (Part II) features 31 articles on key areas of AI and data science, including machine learning and big data, computer vision and image processing, explainability, data privacy, and fairness in trustworthy AI, as well as innovations for health—from data acquisition to AI-driven analysis. These proceedings are intended to serve as a lasting reference and a source of inspiration for research and applications in AI, data science, and emerging technologies.