Titlebook: Machine Learning for Networking; 6th International Co Éric Renault,Selma Boumerdassi,Paul Mühlethaler Conference proceedings 2024 The Edito

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书目名称Machine Learning for Networking影响因子(影响力)




书目名称Machine Learning for Networking影响因子(影响力)学科排名




书目名称Machine Learning for Networking网络公开度




书目名称Machine Learning for Networking网络公开度学科排名




书目名称Machine Learning for Networking被引频次




书目名称Machine Learning for Networking被引频次学科排名




书目名称Machine Learning for Networking年度引用




书目名称Machine Learning for Networking年度引用学科排名




书目名称Machine Learning for Networking读者反馈




书目名称Machine Learning for Networking读者反馈学科排名

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任命

Calculus

,Data Summarization for Federated Learning,imental results on IID and non-IID datasets show that this approach yields a similar accuracy as training on the full local datasets, but with a significant reduction of runtimes. There is however no clear advantage of data summarization over random sampling.

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Conference proceedings 2024e, during November 28–30, 2023...The 18 full papers included in this book were carefully reviewed and selected from 34 submissions. The conference aims at providing a top forum for researchers and practitioners to present and discuss new trends in machine learning, deep learning, pattern recognition

Introduction

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Amendment

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Detecting Abnormal Authentication Delays In Identity And Access Management Using Machine Learning,model is updated using the derived data set for real-time data classification. The proposed approach is adaptive, meaning that it can automatically adjust to changes in the underlying authentication delay distribution. Our experimental results showed that our approach improves the detection accuracy in real-time deployment scenarios.