Titlebook: Computational Science – ICCS 2023; 23rd International C Jiří Mikyška,Clélia de Mulatier,Peter M.A. Sloot Conference proceedings 2023 The Ed

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Siamese Autoencoder-Based Approach for Missing Data Imputationthods in an experimental setup that comprises 14 heterogeneous datasets of the healthcare domain injected with Missing Not At Random values at a rate between 10% and 60%. The results show that SAEI significantly outperforms all the remaining imputation methods for all experimented settings, achievin

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Data Heterogeneity Differential Privacy: From Theory to Algorithmot add noise when training with it. Based on this observation, we design a ‘Performance Improving’ DP-SGD algorithm: PIDP-SGD. Theoretical and experimental results show that our proposed PIDP-SGD improves the performance significantly.

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Differential Dataset Cartography: Explainable Artificial Intelligence in Comparative Personalized Ses that differ in the type of human context were used: user-annotator, user-author, and user-author-annotator. Our results show that with the new explainable AI method, it is possible to pose new hypotheses explaining differences in the quality of model performance, both at the level of features in t

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