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A General Framework for Imprecise Regression.

, и . FUZZ-IEEE, стр. 1-6. IEEE, (2007)

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Theodor Mathieu

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Herbert Mathieu

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Ilse Mathieu

 

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Possibilistic Inductive Logic Programming., и . ECSQARU, том 3571 из Lecture Notes in Computer Science, стр. 675-686. Springer, (2005)Learning Disentangled Representations via Mutual Information Estimation., , и . CoRR, (2019)Improving Expressivity of Inductive Logic Programming by Learning Different Kinds of Fuzzy Rules., и . Soft Comput., 11 (5): 459-466 (2007)Why Imprecise Regression: A Discussion., и . SMPS, том 77 из Advances in Intelligent and Soft Computing, стр. 527-535. Springer, (2010)Learning First Order Fuzzy Logic Rules., , и . IFSA, том 2715 из Lecture Notes in Computer Science, стр. 702-709. Springer, (2003)Possibilistic KNN Regression Using Tolerance Intervals., , и . IPMU (3), том 299 из Communications in Computer and Information Science, стр. 410-419. Springer, (2012)DP-SGD Without Clipping: The Lipschitz Neural Network Way., , , , , , , , и . CoRR, (2023)Loi de fitts: prédiction du temps de pointage sous forme d'ensembles flous., и . IHM, стр. 3-10. ACM, (2007)Elicitating Sugeno Integrals: Methodology and a Case Study., , , и . ECSQARU, том 5590 из Lecture Notes in Computer Science, стр. 712-723. Springer, (2009)On the Induction of Different Kinds of First-Order Fuzzy Rules., , и . ECSQARU, том 2711 из Lecture Notes in Computer Science, стр. 370-381. Springer, (2003)