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Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
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IEEE Computer Society
, 2022 , Article)
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
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Elsevier B.V.
, 2022 , Article)
Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. It is a promising solution for telemonitoring ...
Robust Decentralized Federated Learning Using Collaborative Decisions
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Federated Learning (FL) has attracted a lot of attention in numerous applications due to recent data privacy regulations and increased awareness about data handling issues, combined with the ever-increasing big-data sizes. ...
Federated Learning Stability Under Byzantine Attacks
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Federated Learning (FL) is a machine learning approach that enables private and decentralized model training. Although FL has been shown to be very useful in several applications, its privacy constraints cause a lack of ...
Towards Secure IoT Networks in Healthcare Applications: A Game Theoretic Anti-Jamming Framework
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
The internet of Things (IoT) is used to interconnect a massive number of heterogeneous resource constrained smart devices. This makes such networks exposed to various types of malicious attacks. In particular, jamming ...