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Titlebook: Relational Calculus for Actionable Knowledge; Michel Barès,éloi Bossé Book 2022 The Editor(s) (if applicable) and The Author(s), under exc

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31#
發(fā)表于 2025-3-26 22:03:56 | 只看該作者
oss other datasets in the domain of fake news. We aim to acquire useful insights into the models’ robustness and generalizability across multiple datasets. We carried out an extensive set of experiments with five deep-learning models and seven datasets. These models are tested within a domain and ac
32#
發(fā)表于 2025-3-27 02:09:42 | 只看該作者
éloi Bossé,Michel Barèsds, . can generate new testflows for attack variants with high accuracy and precision, validated using real-world dataset. By automating the testflow generation, . enhances the effectiveness of threat hunting and frees security professionals to focus on strategic aspects of cybersecurity operations.
33#
發(fā)表于 2025-3-27 09:17:21 | 只看該作者
éloi Bossé,Michel Barèsds, . can generate new testflows for attack variants with high accuracy and precision, validated using real-world dataset. By automating the testflow generation, . enhances the effectiveness of threat hunting and frees security professionals to focus on strategic aspects of cybersecurity operations.
34#
發(fā)表于 2025-3-27 12:20:37 | 只看該作者
éloi Bossé,Michel Barèsbased scams that have a web presence. Given a small scam sample, our model formulates scam-related search queries and uses them on multiple search engines to search for, and collect, potential scam pages. After collecting a sufficiently large corpus of web pages, our model semi-automatically cluster
35#
發(fā)表于 2025-3-27 15:31:47 | 只看該作者
éloi Bossé,Michel Barès incorrectness while maintaining good correctness over multiple adversarial attacks at different perturbation budgets by leveraging the ability to correct errors in the classification process. This provides an alternative classification-with-rejection method which can reduce the amount of additional
36#
發(fā)表于 2025-3-27 18:41:48 | 只看該作者
37#
發(fā)表于 2025-3-28 01:47:30 | 只看該作者
éloi Bossé,Michel Barès incorrectness while maintaining good correctness over multiple adversarial attacks at different perturbation budgets by leveraging the ability to correct errors in the classification process. This provides an alternative classification-with-rejection method which can reduce the amount of additional
38#
發(fā)表于 2025-3-28 02:42:30 | 只看該作者
39#
發(fā)表于 2025-3-28 06:44:19 | 只看該作者
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