Team : LFI - Learning, Fuzzy and Intelligent systems
Axe : AID (👥👥).Team leader :
Christophe Marsala Campus Pierre et Marie Curie 26-00/506
No event planned at present.
Short presentation
The LFI (Learning, Fuzzy and Intelligent Systems) team has been created on January 1st, 2014 from the "Machine Learning and Uncertainty" part of the MALIRE team of the LIP6.
The research of the LFI team is focused on the use of computational intelligence techniques for the design of intelligent systems. In particular, we develop research on the interpretability of artificial intelligence methods in the fields of decision support, data science and machine learning. The scientific and applicative objectives are to design and propose approaches that are both explainable during their construction and during their use. For this, we carry out both fundamental research, for the design of new models or the extension of existing theoretical models to take into account gradual or imperfect knowledge, and research in various application areas.
Computational intelligence. Fuzzy Logic. Machine Learning. Knowledge and model of reasoning. Explainable Artificial Intelligence (XAI).
Selected publications
- M.‑J. Lesot, Ch. Marsala : “Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications: Dedicated to Bernadette Bouchon-Meunier” vol. 394, Studies in Fuzziness and Soft Computing[Lesot 2021]
- B. Bouchon‑Meunier, Ch. Marsala : “Entropy and monotonicity in artificial intelligence” International Journal of Approximate Reasoning, vol. 124, pp. 111-122, (Elsevier)[Bouchon-Meunier 2020d]
- Th. Laugel, M.‑J. Lesot, Ch. Marsala, M. Detyniecki : “Issues with post-hoc counterfactual explanations: a discussion” ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, United States[Laugel 2019a]
- Th. Laugel, M.‑J. Lesot, Ch. Marsala, X. Renard, M. Detyniecki : “The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations” Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI-19}, Macao, Macao, pp. 2801-2807, (International Joint Conferences on Artificial Intelligence Organization)[Laugel 2019b]
- B. Bouchon‑Meunier : “Uncertainty management, probabilities, entropy and other paradigms” chapter in Uncertainty Modeling, vol. 683, Studies in Computational Intelligence, (Springer)[Bouchon-Meunier 2017b]
- G. Moyse, M.‑J. Lesot : “Linguistic summaries of locally periodic time series” Fuzzy Sets and Systems, vol. 285, pp. 94-117, (Elsevier)[Moyse 2016]
- A. Guillon, M.‑J. Lesot, Ch. Marsala, N. Pal : “Proximal Optimization for Fuzzy Subspace Clustering” Information Processing and Management of Uncertainty in Knowledge-Based Systems 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I, vol. 610, Communications in Computer and Information Science, Eindhoven, Netherlands, pp. 675-686[Guillon 2016b]
- S. Lefort, M.‑J. Lesot, E. Zibetti, Ch. Tijus, M. Detyniecki : “How much is " about " ? Fuzzy interpretation of approximate numerical expressions” 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'16), Eindhoven, Netherlands[Lefort 2016a]
- B. Legastelois, M.‑J. Lesot, A. Revault D'Allonnes : “Negation of graded beliefs” Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016, Eindhoven, Netherlands[Legastelois 2016c]
- X. Renard, M. Rifqi, G. Fricout, M. Detyniecki : “EAST representation: fast discovery of discriminant temporal patterns from time series” ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data, Riva Del Garda, Italy[Renard 2016]
Contact
Christophe.Marsala (at) nulllip6.fr