Mr Ruiyu Wang
- Research Associate (Autonomous Systems & Connectivity)
email:
Ruiyu.Wang@glasgow.ac.uk
The University of Glasgow uses cookies for analytics. Find out more about our Privacy policy.
Necessary cookies enable core functionality. The website cannot function properly without these cookies, and can only be disabled by changing your browser preferences.
Analytical cookies help us improve our website. We use Google Analytics. All data is anonymised.
Hotjar and Clarity help us to understand our users’ behaviour by visually representing their clicks, taps and scrolling. All data is anonymised.
email:
Ruiyu.Wang@glasgow.ac.uk
Zhang, B., Wang, R., Xu, H. , Zhang, X. and Zhang, L. (2022) DISTERNING: distance estimation using machine learning approach for COVID-19 contact tracing and beyond. IEEE Journal on Selected Areas in Communications, 40(11), pp. 3207-3223. (doi: 10.1109/JSAC.2022.3214277)
Weng, S., Zhang, L. , Feng, D., Feng, C., Wang, R., Valente Klaine, P. and Imran, M. A. (2022) Privacy-Preserving Federated Learning based on Differential Privacy and Momentum Gradient Descent. In: IEEE World Congress on Computational Intelligence (WCCI 2022), Padua, Italy, 18-23 Jul 2022, ISBN 9781728186719 (doi: 10.1109/IJCNN55064.2022.9889795)
Zhang, B., Wang, R., Xu, H. , Zhang, X. and Zhang, L. (2022) DISTERNING: distance estimation using machine learning approach for COVID-19 contact tracing and beyond. IEEE Journal on Selected Areas in Communications, 40(11), pp. 3207-3223. (doi: 10.1109/JSAC.2022.3214277)
Weng, S., Zhang, L. , Feng, D., Feng, C., Wang, R., Valente Klaine, P. and Imran, M. A. (2022) Privacy-Preserving Federated Learning based on Differential Privacy and Momentum Gradient Descent. In: IEEE World Congress on Computational Intelligence (WCCI 2022), Padua, Italy, 18-23 Jul 2022, ISBN 9781728186719 (doi: 10.1109/IJCNN55064.2022.9889795)