Hoang, Dinh Thai

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

Lim, W. Y. B., Luong, N. C., Hoang, D. T., Jiao, Y., Liang, Y.-C., Yang, Q., Niyato, D., & Miao, C. (2020) · IEEE Communications Surveys & Tutorials

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 2,565

Ambient Backscatter Communications: A Contemporary Survey

Van Huynh, N., Hoang, D. T., Lu, X., Niyato, D., Wang, P., & Kim, D. I. (2018) · IEEE Communications Surveys & Tutorials

Energy Harvesting in Wireless NetworksWireless Communication Security Techniques

Cited by 932

Energy Demand Prediction with Federated Learning for Electric Vehicle Networks

Saputra, Y. M., Hoang, D. T., Nguyen, D. N., Dutkiewicz, E., Mueck, M. D., & Srikanteswara, S. (2019) · 2019 IEEE Global Communications Conference (GLOBECOM)

Electric Vehicles and InfrastructureEnergy Load and Power Forecasting

Cited by 277

Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning

Ilahi, I., Usama, M., Qadir, J., Janjua, M. U., Al-Fuqaha, A., Hoang, D. T., & Niyato, D. (2022) · IEEE Transactions on Artificial Intelligence

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 170

Federated Learning Meets Contract Theory: Economic-Efficiency Framework for Electric Vehicle Networks

Saputra, Y. M., Nguyen, D. N., Hoang, D. T., Vu, T. X., Dutkiewicz, E., & Chatzinotas, S. (2022) · IEEE Transactions on Mobile Computing

Electric Vehicles and InfrastructureSmart Grid Energy Management

Cited by 76

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Luong, N. C., Hoang, D. T., Gong, S., Niyato, D., Wang, P., Liang, Y.-C., & Kim, D. I. (2018) · arXiv

Reinforcement Learning in RoboticsSoftware-Defined Networks and 5G

Cited by 17