Related references
Note: Only part of the references are listed.Federated learning for malware detection in IoT devices
Valerian Rey et al.
COMPUTER NETWORKS (2022)
AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus
Ali Al-Laith et al.
APPLIED SCIENCES-BASEL (2021)
Digital Twin for Intelligent Context-Aware IoT Healthcare Systems
Haya Elayan et al.
IEEE INTERNET OF THINGS JOURNAL (2021)
Federated Learning in Vehicular Networks: Opportunities and Solutions
Jason Posner et al.
IEEE NETWORK (2021)
Battery-constrained federated edge learning in UAV-enabled IoT for B5G/6G networks
Shunpu Tang et al.
PHYSICAL COMMUNICATION (2021)
On confidentiality-critical machine learning applications in industry
Werner Zellinger et al.
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING (ISM 2020) (2021)
Scheduling Policies for Federated Learning in Wireless Networks
Howard H. Yang et al.
IEEE TRANSACTIONS ON COMMUNICATIONS (2020)
Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
Sumudu Samarakoon et al.
IEEE TRANSACTIONS ON COMMUNICATIONS (2020)
Distributed learning on 20 000+lung cancer patients - The Personal Health Train
Timo M. Deist et al.
RADIOTHERAPY AND ONCOLOGY (2020)
How Machine Learning Will Transform Biomedicine
Jeremy Goecks et al.
CELL (2020)
DRL plus FL: An intelligent resource allocation model based on deep reinforcement learning for Mobile Edge Computing
Nanliang Shan et al.
COMPUTER COMMUNICATIONS (2020)
Remaining useful life prediction based on state assessment using edge computing on deep learning
Hsin-Yao Hsu et al.
COMPUTER COMMUNICATIONS (2020)
Highly efficient federated learning with strong privacy preservation in cloud computing
Chen Fang et al.
COMPUTERS & SECURITY (2020)
Federated Learning: Challenges, Methods, and Future Directions
Tian Li et al.
IEEE SIGNAL PROCESSING MAGAZINE (2020)
Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles
Yunlong Lu et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)
A Crowdsourcing Framework for On-Device Federated Learning
Shashi Raj Pandey et al.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2020)
Adaptive privacy-preserving federated learning
Xiaoyuan Liu et al.
PEER-TO-PEER NETWORKING AND APPLICATIONS (2020)
The extensible Data-Brain model: Architecture, applications and directions
Hongzhi Kuai et al.
JOURNAL OF COMPUTATIONAL SCIENCE (2020)
Federated Learning With Cooperating Devices: A Consensus Approach for Massive IoT Networks
Stefano Savazzi et al.
IEEE INTERNET OF THINGS JOURNAL (2020)
Preserving Data Privacy via Federated Learning: Challenges and Solutions
Zengpeng Li et al.
IEEE CONSUMER ELECTRONICS MAGAZINE (2020)
Blockchain-based database in an IoT environment: challenges, opportunities, and analysis
Lewis Tseng et al.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2020)
EaSTFLy: Efficient and secure ternary federated learning
Ye Dong et al.
COMPUTERS & SECURITY (2020)
Blockchained On-Device Federated Learning
Hyesung Kim et al.
IEEE COMMUNICATIONS LETTERS (2020)
Federated Learning for Data Privacy Preservation in Vehicular Cyber-Physical Systems
Yunlong Lu et al.
IEEE NETWORK (2020)
On Safeguarding Privacy and Security in the Framework of Federated Learning
Chuan Ma et al.
IEEE NETWORK (2020)
Robust Federated Learning With Noisy Communication
Fan Ang et al.
IEEE TRANSACTIONS ON COMMUNICATIONS (2020)
Federated Learning With Blockchain for Autonomous Vehicles: Analysis and Design Challenges
Shiva Raj Pokhrel et al.
IEEE TRANSACTIONS ON COMMUNICATIONS (2020)
Blockchain and Federated Learning for Privacy-Preserved Data Sharing in Industrial IoT
Yunlong Lu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Accelerating Federated Learning via Momentum Gradient Descent
Wei Liu et al.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2020)
Improving TCP Performance Over WiFi for Internet of Vehicles: A Federated Learning Approach
Shiva Raj Pokhrel et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Alejandro Barredo Arrieta et al.
INFORMATION FUSION (2020)
A training-integrity privacy-preserving federated learning scheme with trusted execution environment
Yu Chen et al.
INFORMATION SCIENCES (2020)
Privacy-preserving federated k-means for proactive caching in next generation cellular networks
Yang Liu et al.
INFORMATION SCIENCES (2020)
Decentralized Privacy Using Blockchain-Enabled Federated Learning in Fog Computing
Youyang Qu et al.
IEEE INTERNET OF THINGS JOURNAL (2020)
Blockchain and federated learning-based distributed computing defence framework for sustainable society
Pradip Kumar Sharma et al.
SUSTAINABLE CITIES AND SOCIETY (2020)
Key protected classification for collaborative learning
Mert Bulent Sariyildiz et al.
PATTERN RECOGNITION (2020)
Federated and secure cloud services for building medical image classifiers on an intercontinental infrastructure
Ignacio Blanquer et al.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)
A Sustainable Incentive Scheme for Federated Learning
Han Yu et al.
IEEE INTELLIGENT SYSTEMS (2020)
Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge Based Framework
Qiong Wu et al.
IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY (2020)
The Study for Public Management Policy Utility Evaluation and Optimization System Under the Framework of Social Computing Perspective
Le Chen et al.
IEEE INTELLIGENT SYSTEMS (2020)
A review of applications in federated learning
Li Li et al.
COMPUTERS & INDUSTRIAL ENGINEERING (2020)
Trustworthy and sustainable smart city services at the edge
Yaser Jararweh et al.
SUSTAINABLE CITIES AND SOCIETY (2020)
Deep Learning for Edge Computing Applications: A State-of-the-Art Survey
Fangxin Wang et al.
IEEE ACCESS (2020)
Federated Cooperation and Augmentation for Power Allocation in Decentralized Wireless Networks
Mu Yan et al.
IEEE ACCESS (2020)
Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems
Bouziane Brik et al.
IEEE ACCESS (2020)
CEFL: Online Admission Control, Data Scheduling, and Accuracy Tuning for Cost-Efficient Federated Learning Across Edge Nodes
Zhi Zhou et al.
IEEE INTERNET OF THINGS JOURNAL (2020)
Personalized Federated Learning With Differential Privacy
Rui Hu et al.
IEEE INTERNET OF THINGS JOURNAL (2020)
Federated Learning for Vehicular Internet of Things: Recent Advances and Open Issues
Zhaoyang Du et al.
IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY (2020)
A unified data security framework for federated prognostics and health management in smart manufacturing
Behrad Bagheri et al.
MANUFACTURING LETTERS (2020)
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2020)
Federated Learning-Based Cognitive Detection of Jamming Attack in Flying Ad-Hoc Network
Nishat Mowla et al.
IEEE ACCESS (2020)
Privacy-Preserving Asynchronous Federated Learning Mechanism for Edge Network Computing
Xiaofeng Lu et al.
IEEE ACCESS (2020)
Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications
Mohammed Aledhari et al.
IEEE ACCESS (2020)
Federated Learning With Differential Privacy: Algorithms and Performance Analysis
Kang Wei et al.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2020)
VerifyNet: Secure and Verifiable Federated Learning
Guowen Xu et al.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2020)
Symposium review: Challenges and opportunities for evaluating and using the genetic potential of dairy cattle in the new era of sensor data from automation
N. Gengler
JOURNAL OF DAIRY SCIENCE (2019)
Federated Machine Learning: Concept and Applications
Qiang Yang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2019)
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2019)
In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
Xiaofei Wang et al.
IEEE NETWORK (2019)
Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records
Li Huang et al.
JOURNAL OF BIOMEDICAL INFORMATICS (2019)
Accelerating the Translation of Artificial Intelligence From Ideas to Routine Clinical Workflow
MingDe Lin
ACADEMIC RADIOLOGY (2019)
Privacy-aware service placement for mobile edge computing via federated learning
Yongfeng Qian et al.
INFORMATION SCIENCES (2019)
An overview of deep learning in medical imaging focusing on MRI
Alexander Selvikvag Lundervold et al.
ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK (2019)
Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems
Boyi Liu et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2019)
Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems
Boyi Liu et al.
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2019)
Deep-space applications for point-of-care technologies
Gary E. Strangman et al.
CURRENT OPINION IN BIOMEDICAL ENGINEERING (2019)
Privacy preserving multi-party computation delegation for deep learning in cloud computing
Xu Ma et al.
INFORMATION SCIENCES (2018)
Federated learning of predictive models from federated Electronic Health Records
Theodora S. Brisimi et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2018)
MeShClust: an intelligent tool for clustering DNA sequences
Benjamin T. James et al.
NUCLEIC ACIDS RESEARCH (2018)
A Formal Foundation for Secure Remote Execution of Enclaves
Pramod Subramanyan et al.
CCS'17: PROCEEDINGS OF THE 2017 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (2017)
Densely Connected Convolutional Networks
Gao Huang et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)
Representation Learning: A Review and New Perspectives
Yoshua Bengio et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2013)