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Estimating Relevant Input Dimensions for Self-organizing Algorithms., и . WSOM, стр. 173-180. Springer, (2001)Mitigating Concept Drift via Rejection., , и . ICANN (1), том 11139 из Lecture Notes in Computer Science, стр. 456-467. Springer, (2018)On Approximate Learning by Multi-layered Feedforward Circuits., и . ALT, том 1968 из Lecture Notes in Computer Science, стр. 264-278. Springer, (2000)Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks., , и . ICPRAM, стр. 296-303. SCITEPRESS, (2024)So Can We Use Intrinsic Bias Measures or Not?, , , и . ICPRAM, стр. 403-410. SCITEPRESS, (2023)Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation., , и . ICDM, стр. 1096-1101. IEEE, (2019)08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications., , , и . Recurrent Neural Networks, том 08041 из Dagstuhl Seminar Proceedings, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany, (2008)Extending Drift Detection Methods to Identify When Exactly the Change Happened., , и . IWANN (1), том 14134 из Lecture Notes in Computer Science, стр. 92-104. Springer, (2023)Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces., , , и . DeLFI, том P-207 из LNI, стр. 27-38. GI, (2012)Improving Zorro Explanations for Sparse Observations with Dense Proxy Data., , и . ESANN, (2022)