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Titlebook: Artificial Intelligence Security and Privacy; First International Jaideep Vaidya,Moncef Gabbouj,Jin Li Conference proceedings 2024 The Edi

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41#
發(fā)表于 2025-3-28 16:36:23 | 只看該作者
42#
發(fā)表于 2025-3-28 19:28:42 | 只看該作者
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發(fā)表于 2025-3-29 00:44:27 | 只看該作者
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發(fā)表于 2025-3-29 06:30:49 | 只看該作者
,Rethinking Distribution Alignment for?Inter-class Fairness,can significantly improve performance in class imbalance tasks in terms of both accuracy and recall metrics when integrated with advanced SSL algorithms. Although the idea of BTDA is not complex, it can show advanced performance on datasets such as CIFAR and SVHN.
45#
發(fā)表于 2025-3-29 08:35:16 | 只看該作者
,Online Learning Behavior Analysis and?Achievement Prediction with?Explainable Machine Learning,chieved, we gain reasonable explanation on the influence factors hander the learning achievement, and predict the learning achievements with the explainable machine learning models. Finally, some suggestions are put forward to improve students’ learning behaviors, aiming to promote the quality of on
46#
發(fā)表于 2025-3-29 11:29:12 | 只看該作者
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發(fā)表于 2025-3-29 16:37:13 | 只看該作者
A Graph-Based Vertical Federation Broad Learning System,randomly generated during the initial graph establishment phase. There is no guidance for extracting features, and the quality of the extracted features is not guaranteed. Therefore, this paper introduces the extreme learning auto-encoder into the graph-based vertical federation broad learning syste
48#
發(fā)表于 2025-3-29 23:10:57 | 只看該作者
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發(fā)表于 2025-3-30 02:14:07 | 只看該作者
50#
發(fā)表于 2025-3-30 06:50:27 | 只看該作者
An Improved Prototypical Network for Endoscopic Grading of Intestinal Metaplasia,m support sets. Then, the average value of features is calculated as the prototype of each category. Third, the features of the query set images are extracted using the pre-trained ViT as well. After the distances between them and prototypes are calculated for predicting the category. Finally, we co
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