Y. Hu, X. Wang, and W. Saad, "Distributed and Distribution-Robust Meta Reinforcement Learning (D2-RMRL) for Data Pre-storing and Routing in Cube Satellite Networks", IEEE Journal on Selected Topics in Signal Processing (JSTSP), Special Issue on Distributed Signal Processing for Edge Learning in B5G IoT Networks, to appear, 2022.
Y. Wang, Y. Hu, Z. Yang, W. Saad, K.-K. Wong, and V. Friderikos,"Learning from Images: Proactive Caching with Parallel Convolutional Neural Networks", IEEE Transactions on Mobile Computing, to appear, 2022.
M. N. H. Nguyen, S. R. Pandey, T. N. Dang, E.-N. Huh, C. S. Hong, M. H. Tran, and W. Saad, "Self-organizing Democratized Learning: Towards Large-scale Distributed Learning Systems", IEEE Transactions on Neural Networks and Learning Systems, to appear, 2022.
S. Wang, M Chen, Z. Yang, C. Yin, W. Saad, S. Cui, and H. V. Poor, "Distributed Reinforcement Learning for Age of Information Minimization in Real-Time IoT Systems", IEEE Journal on Selected Topics in Signal Processing (JSTSP), Special Issue on Distributed Machine Learning for Wireless Communication, vol. 16, no. 3, pp. 501 - 515, April 2022.
S. Wang, M. Chen, C. Yin, W. Saad, C. S. Hong, S. Cui, and H. V. Poor, "Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks", IEEE Internet of Things Journal, May, 2021.
S. Munir, N. H. Tran, W. Saad, and C. S. Hong, "Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems", IEEE Transactions on Network and Service Management, September, 2021
Z. Yang, M. Chen, W. Saad, C. S. Hong, and M. Shikh-Bahaei, "Energy Efficient Federated Learning Over Wireless Communication Networks", IEEE Transactions on Wireless Communications, March, 2021.
M. Chen, W. Saad, and C. Yin, "Liquid State Machine Learning for Resource and Cache Management in LTE-U Unmanned Aerial Vehicle (UAV) Networks", IEEE Transactions on Wireless Communications, vol. 18, no. 3, pp. 1504-1517, March 2019.
Q. Zhang, W. Saad, and M. Bennis, "Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV", in Proc. of the IEEE Global Communications Conference (GLOBECOM), Next Generation Networking and Internet Symposium, Taipei, Taiwan, December 2020.
Q. Zhang, W. Saad, and M. Bennis, "Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV", in Proc. of the IEEE Global Communications Conference (GLOBECOM), Next Generation Networking and Internet Symposium, Taipei, Taiwan, December 2020.
L. U. Khan, S. R. Pandey, N. H. Tran, W. Saad, Z. Han, M. N. H. Nguyen, and C. S. Hong, "Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism", IEEE Communications Magazine, Data Science/Artificial Intelligence Series, vol. 58, no. 10, pp. 88 - 93, October 2020.
S. Ali, A. Ferdowsi, W. Saad, N. Rajatheva, and J. Haapola, "Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications", IEEE Transactions on Communications, vol. 68, no. 8, pp. 5072 - 5086, August 2020.
X. Zhang, Y. Xiao, Q. Li, and W. Saad, "Deep Reinforcement Learning for Fog Computing-based Vehicular System with Multi-operator Support", in Proc. of the IEEE International Conference on Communications (ICC), SAC Cloud & Fog Computing, Networking, and Storage Track, Dublin, Ireland, June 2020.
M. Naderi Soorki, W. Saad, and M. Bennis, "Ultra-Reliable Millimeter-Wave Communications using an Artificial Intelligence-Powered Reflector", in Proc. of the IEEE Global Communications Conference (GLOBECOM), Wireless Communications Symposium, Waikoloa, HI, USA, December 2019.
A. T. Z. Kasgari, W. Saad, and M. Debbah, "Human-in-the-Loop Wireless Communications: Machine Learning and Brain-Aware Resource Management", IEEE Transactions on Communications, vol. 67, no. 11, pp. 7727-7743, November. 2019.
U. Challita, L. Dong, and W. Saad, "Proactive Resource Management for LTE in Unlicensed Spectrum: A Deep Learning Perspective", IEEE Transactions on Wireless Communications, vol. 17, no. . 7, pp. 4674 - 4689, July 2018.
Q. Zhang, M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, "Machine Learning for Predictive On-Demand Deployment of UAVs for Wireless Communications", in Proc. of the IEEE Global Communications Conference (GLOBECOM), Green Communications Systems and Networks Symposium, Abu Dhabi, UAE, December 2018.
S. Ali, W. Saad, and N. Rajatheva, "A Directed Information Learning Framework for Event-Driven M2M Traffic Prediction", IEEE Communications Letters, vol. 22, no. 11, pp. 2378 - 2381, November 2018.
U. Challita, L. Dong, and W. Saad, "Proactive Resource Management for LTE in Unlicensed Spectrum: A Deep Learning Perspective", IEEE Transactions on Wireless Communications, vol. 17, no. 7, pp. 4674 - 4689, July 2018.
A. Taleb Zadeh Kasgari, B. Maham, H. Kebriaei, and W. Saad, "Dynamic Learning for Distributed Power Control in Underlaid Cognitive Radio Networks", in Proc. 14th International Wireless Communications & Mobile Computing Conference (IWCMC), Limasol, Cyprus, June 2018.
K. Hamidouche, A. Taleb Zadeh Kasgari, W. Saad, M. Bennis, and M. Debbah, "Collaborative Artificial Intelligence (AI) for User-Cell Association in Ultra-Dense Cellular Systems", in Proc. of the IEEE International Conference on Communications (ICC), Workshop on Promises and Challenges of Machine Learning in Communication Networks, Kansas City, MO, USA, May 2018.
M. Chen, W. Saad, and C. Yin, "Echo State Learning for Wireless Virtual Reality Resource Allocation in UAV-enabled LTE-U Networks", in Proc. of the IEEE International Conference on Communications (ICC), Cognitive Radio Networking Symposium, Kansas City, MO, USA, May 2018.
K. Hamidouche, A. Taleb Zadeh Kasgari, W. Saad, M. Bennis, and M. Debbah, "Collaborative Artificial Intelligence (AI) for User-Cell Association in Ultra-Dense Cellular Systems", in Proc. of the IEEE International Conference on Communications (ICC), Workshop on Promises and Challenges of Machine Learning in Communication Networks, Kansas City, MO, USA, May 2018.
A. Taleb Zadeh Kasgari, W. Saad, and M. Debbah, "Brain-Aware Wireless Networks: Learning and Resource Management", in Proc. of the 51st Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, November 2017.
M. Chen, W. Saad, C. Yin, and M. Debbah, "Echo State Networks for Proactive Caching in Cloud-Based Radio Access Networks with Mobile Users", IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3520 - 3535, June 2017.
U. Challita, L. Dong, and W. Saad, "Deep Learning for Proactive Resource Allocation in LTE-U Networks", in Proc. of European Wireless, Dresden, Germany, May 2017.
A. Hajijamali Arani, A. Mehbodniya, M. J. Omidi, F. Adachi, W. Saad, and I. Guvenc, "Distributed Learning for Energy-Efficient Resource Management in Self-Organizing Heterogeneous Networks", IEEE Transactions on Vehicular Technology, vol. 66, no. 10, pp. 9287 - 9303, October 2017.
M. Chen, W. Saad, and C. Lin, "Echo State Networks for Self-Organizing Resource Allocation in LTE-U with Uplink-Downlink Decoupling", IEEE Transactions on Wireless Communications, vol. 16, no. 1, pp. 3-16, January 2017.
M. Chen, W. Saad, C. Yin, and M. Debbah, "Echo State Networks for Proactive Caching and Content Prediction in Cloud Radio Access Networks," in Proc. of the IEEE Global Communications Conference (GLOBECOM), Workshop on 5G RAN Design, Washington, DC, USA, December 2016.