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Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features., , , и . ESANN, (2022)Investigation of Activation Functions for Generalized Learning Vector Quantization., , , , и . WSOM+, том 976 из Advances in Intelligent Systems and Computing, стр. 179-188. Springer, (2019)Monitoring of Physiological Parameters of Patients and Therapists During Psychotherapy Sessions Using Self-Organizing Maps., , , и . ANNIMAB, стр. 221-226. Springer, (2000)Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms., , и . NeurIPS, (2020)Functional relevance learning in learning vector quantization for hyperspectral data., и . WHISPERS, стр. 1-4. IEEE, (2011)Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data., , , и . ICMLA, стр. 374-379. IEEE Computer Society, (2004)Supervised neural gas for learning vector quantization, , и . (2002)The Coming of Age of Interpretable and Explainable Machine Learning Models., , , и . ESANN, (2021)Possibilistic Classification Learning Based on Contrastive Loss in Learning Vector Quantizer Networks., , и . ICAISC (1), том 12854 из Lecture Notes in Computer Science, стр. 156-167. Springer, (2021)A Mathematical Model for Optimum Error-Reject Trade-Off for Learning of Secure Classification Models in the Presence of Label Noise During Training., , и . ICAISC (1), том 12415 из Lecture Notes in Computer Science, стр. 547-554. Springer, (2020)