Titlebook: ECML PKDD 2020 Workshops; Workshops of the Eur Irena Koprinska,Michael Kamp,Jon Atle Gulla Conference proceedings 2020 Springer Nature Swit

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圆桶

Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networksrency and trust can be ensured in the underlying distributions and relationships of the resulting synthetic datasets. What is more, these datasets offer a strong level of privacy through lower risks of identifying real patients.

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GIST

Resource-Constrained On-Device Learning by Dynamic Averagingr processors typically only have integer processing capabilities. This paper investigates an approach to communication-efficient on-device learning of integer exponential families that can be executed on low-power processors, is privacy-preserving, and effectively minimizes communication. The empiri

Hyperalgesia

MitM Attack Detection in BLE Networks Using Reconstruction and Classification Machine Learning Technus data batches. We then applied a classification method based on Text-CNN technique to classify packets as normal or attack inside each suspicious batch. Our model reconstruction results show that we are able to discriminate normal and attack models with high precision and our classification method

jocular

Hybrid Connection and Host Clustering for Community Detection in Spatial-Temporal Network Datay unsupervised, our method outperforms many existing approaches. To the best of our knowledge, the only approaches with comparable performance require manual filtering of connections and feature engineering steps. In contrast, our method is applied to raw network traffic. We apply our pipeline to th

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Conference proceedings 2020DML 2020, Second  International Workshop  on  eXplainable  Knowledge  Discovery in  Data Mining, XKDD 2020; 8th International Workshop on News Recommendation and Analytics, INRA 2020. .The papers from INRA 2020 are published open access and licensed under the terms of the Creative Commons Attributio

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1865-0929 ws Recommendation and Analytics, INRA 2020. .The papers from INRA 2020 are published open access and licensed under the terms of the Creative Commons Attributio978-3-030-65964-6978-3-030-65965-3Series ISSN 1865-0929 Series E-ISSN 1865-0937