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Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.3027980
Abstract: As an important driving factor of emerging Internet-of-Things (IoT) applications, machine learning algorithms are currently facing the challenge of how to “clean” data noise, that is introduced during the training process (e.g., asynchronous execution and…
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Keywords:
edge intelligence;
data cleaning;
federated data;
privacy ... See more keywords
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Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3215192
Abstract: Federated learning breaks down data silos and promotes the intelligence of the Industrial Internet of Things (IIoT). However, the principal–agent architecture commonly used in federated learning not only increases the cost but also fails to…
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Keywords:
data sharing;
federated data;
iiot;
secure trusted ... See more keywords
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Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3077044
Abstract: Modern data analysis applications require the ability to provide on-demand integration of data sources while offering a flexible and user-friendly query interface. Traditional techniques for answering queries using views, focused on a rather static setting,…
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Keywords:
federated data;
graph driven;
driven federated;
data management ... See more keywords
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Published in 2022 at "ERJ Open Research"
DOI: 10.1183/23120541.00168-2022
Abstract: Real-world evidence from multinational disease registries is becoming increasingly important not only for confirming the results of randomised controlled trials, but also for identifying phenotypes, monitoring disease progression, predicting response to new drugs and early…
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Keywords:
federated data;
registries allow;
disease;
disease registries ... See more keywords