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This book presents various effective schemes from the perspectives of algorithms, architectures, privacy, and security to enable scalable and trustworthy Federated Edge Learning (FEEL).
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This monograph introduces the field of bisociative literature-based discovery (LBD) by first explaining the underlying LBD principles and techniques, followed by the presentation of bisociative LBD techniques and applications developed by the authors.
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With an entire section dedicated to synthetic data, it explains how artificial data can be used to train effective models while safeguarding user privacy.
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This CCIS 2538 volume constitutes the proceedings of First and Second International Conference on Advancements in Machine Learning, ICCAML 2024, in Pune, India, during February 28–29, 2024. The 19 full papers are carefully reviewed and selected from 173 submissions.
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color: black;">Learning Management SystemsMachine Learning
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The two volume set LNCS 15937 + 15938 constitutes the proceedings of the... Læs mere
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The two volume set LNCS 15937 + 15938 constitutes the proceedings of the... Læs mere
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The two-volume set constitutes the proceedings of the Second... Læs mere
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The proceedings focus on AI for Healthcare, AI for Business and Finance, AI for Defense and Information Security, AI for Agriculture, AI for Education.