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Investigation of Activation Functions for Generalized Learning Vector Quantization.

, , , , and . WSOM+, volume 976 of Advances in Intelligent Systems and Computing, page 179-188. Springer, (2019)

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Investigation of Activation Functions for Generalized Learning Vector Quantization., , , , and . WSOM+, volume 976 of Advances in Intelligent Systems and Computing, page 179-188. Springer, (2019)Functional relevance learning in learning vector quantization for hyperspectral data., and . WHISPERS, page 1-4. IEEE, (2011)Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data., , , and . ICMLA, page 374-379. IEEE Computer Society, (2004)Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features., , , and . ESANN, (2022)Monitoring of Physiological Parameters of Patients and Therapists During Psychotherapy Sessions Using Self-Organizing Maps., , , and . ANNIMAB, page 221-226. Springer, (2000)Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms., , and . NeurIPS, (2020)Possibilistic Classification Learning Based on Contrastive Loss in Learning Vector Quantizer Networks., , and . ICAISC (1), volume 12854 of Lecture Notes in Computer Science, page 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., , and . ICAISC (1), volume 12415 of Lecture Notes in Computer Science, page 547-554. Springer, (2020)ToF/Radar early feature-based fusion system for human detection and tracking., , , , , , and . ICIT, page 942-949. IEEE, (2021)The Coming of Age of Interpretable and Explainable Machine Learning Models., , , and . ESANN, (2021)