1.5k citations · 5k across the 30 of their papers we have counts for
9 papers · 1 filter
Federated Learning for Cyber Physical Systems: A Comprehensive Survey
Minh K. Quan, Pubudu N. Pathirana, Mayuri Wijayasundara +5
The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliabili…
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data
Kanishka Ranaweera, Dinh C. Nguyen, Pubudu N. Pathirana +4
In the era of data-driven machine-learning applications, privacy concerns and the scarcity of labeled data have become paramount challenges. These challenges are particularly prono…
Federated Learning with Differential Privacy: An Utility-Enhanced Approach
Kanishka Ranaweera, Dinh C. Nguyen, Pubudu N. Pathirana +4
Federated learning has emerged as an attractive approach to protect data privacy by eliminating the need for sharing clients' data while reducing communication costs compared with…
Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems
Shiying Zhang, Jun Li, Long Shi +5
Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT). Nonetheles…
Holistic Survey of Privacy and Fairness in Machine Learning
Sina Shaham, Arash Hajisafi, Minh K Quan +6
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the…
Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework
Van-Dinh Nguyen, Thang X. Vu, Nhan Thanh Nguyen +6
To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open R…
Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing
Dinh C. Nguyen, Seyyedali Hosseinalipour, David J. Love +2
In this paper, we study a new latency optimization problem for blockchain-based federated learning (BFL) in multi-server edge computing. In this system model, distributed mobile de…
Federated Learning for Smart Healthcare: A Survey
Dinh C. Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana +5
Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI techniques…
Federated Learning for Industrial Internet of Things in Future Industries
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana +4
The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems and becomes a key enabler for future industries. Recently,…