Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2024 The Editor(s) (if applicable) and The Aut

Exclaim

Adversarial Robustness of Multi-bit Convolutional Neural Networks, with a slight degradation of natural accuracy (–2.4pp) when compared to a 2-bit fixed-point quantized implementation of ResNet-20 on CIFAR-10. Similar observations hold for deeper and wider ResNets trained on different datasets, such as CIFAR-100 and ImageNet. Second, this work shows that the defen

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CRUMB

Grouping Shapley Value Feature Importances of Random Forests for Explainable Yield Prediction, algorithm to compute them efficiently on tree structures. We provide a blueprint for designing swarm plots that combine many local explanations for global understanding. Extensive evaluation of two different yield prediction problems shows the worth of our approach and demonstrates how we can enabl

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預(yù)測

ABHOR

Application of Mean-Variance Cloning Technique to Investigate the Comparative Performance Analysis ence the computational time of the classifiers. The results revealed that the Fisher linear classification method (FLCM) performed comparably for imbalanced and balanced data and outperformed the nearest mean classifier (NMC) and the independent classification rule (ICR). The study demonstrated that

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Arthur Marzinkowski,Salem Benferhat,Anastasia Paparrizou,Cédric Piette

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