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Aristeidis Karras, Christos Karras, Konstantinos C. Giotopoulos, Dimitrios Tsolis, Konstantinos Oikonomou and Spyros Sioutas
Federated learning (FL) has emerged as a promising technique for preserving user privacy and ensuring data security in distributed machine learning contexts, particularly in edge intelligence and edge caching applications. Recognizing the prevalent chall...
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Zhiguo Liang, Lijun Zhang and Xizhe Wang
Since failure of steam turbines occurs frequently and can causes huge losses for thermal plants, it is important to identify a fault in advance. A novel clustering fault diagnosis method for steam turbines based on t-distribution stochastic neighborhood ...
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Xiaochun Sun, Chenmou Wu and Shuqun Yang
With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in com...
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Fei Yan, Hui Zhang, Yaogen Li, Yongjia Yang and Yinping Liu
Raw image classification datasets generally maintain a long-tailed distribution in the real world. Standard classification algorithms face a substantial issue because many labels only relate to a few categories. The model learning processes will tend tow...
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Elnaz Ghanbary Kalajahi, Mehran Mahboubkhah and Ahmad Barari
Closed-loop manufacturing is crucial in Industry 4.0, since it provides an online detection?correction cycle to optimize the production line by using the live data provided from the product being manufactured. By integrating the inspection system and man...
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