Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and trends® in machine learning 14 (1–2), 1-210, 2021 | 6069 | 2021 |
A vision of 6G wireless systems: Applications, trends, technologies, and open research problems W Saad, M Bennis, M Chen IEEE network 34 (3), 134-142, 2019 | 3904 | 2019 |
A tutorial on UAVs for wireless networks: Applications, challenges, and open problems M Mozaffari, W Saad, M Bennis, YH Nam, M Debbah IEEE communications surveys & tutorials 21 (3), 2334-2360, 2019 | 2665 | 2019 |
Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks E Bastug, M Bennis, M Debbah IEEE Com. Mag. SI Context Awareness, 2014 | 1330 | 2014 |
Unmanned aerial vehicle with underlaid device-to-device communications: Performance and tradeoffs M Mozaffari, W Saad, M Bennis, M Debbah IEEE Transactions on Wireless Communications 15 (6), 3949-3963, 2016 | 1297 | 2016 |
Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage M Mozaffari, W Saad, M Bennis, M Debbah IEEE Communications Letters 20 (8), 1647-1650, 2016 | 1151 | 2016 |
Mobile unmanned aerial vehicles (UAVs) for energy-efficient Internet of Things communications M Mozaffari, W Saad, M Bennis, M Debbah IEEE Transactions on Wireless Communications 16 (11), 7574-7589, 2017 | 1119 | 2017 |
Ultrareliable and low-latency wireless communication: Tail, risk, and scale M Bennis, M Debbah, HV Poor Proceedings of the IEEE 106 (10), 1834-1853, 2018 | 1054 | 2018 |
A speculative study on 6G F Tariq, MRA Khandaker, KK Wong, MA Imran, M Bennis, M Debbah IEEE Wireless Communications 27 (4), 118-125, 2020 | 964 | 2020 |
Drone small cells in the clouds: Design, deployment and performance analysis M Mozaffari, W Saad, M Bennis, M Debbah 2015 IEEE global communications conference (GLOBECOM), 1-6, 2015 | 789 | 2015 |
Blockchained on-device federated learning H Kim, J Park, M Bennis, SL Kim IEEE Communications Letters 24 (6), 1279-1283, 2019 | 783 | 2019 |
Communication-efficient on-device machine learning: Federated distillation and augmentation under non-iid private data E Jeong, S Oh, H Kim, J Park, M Bennis, SL Kim arXiv preprint arXiv:1811.11479, 2018 | 680 | 2018 |
Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning X Chen, H Zhang, C Wu, S Mao, Y Ji, M Bennis IEEE Internet of Things Journal 6 (3), 4005-4018, 2018 | 665 | 2018 |
Toward interconnected virtual reality: Opportunities, challenges, and enablers E Bastug, M Bennis, M Médard, M Debbah IEEE Communications Magazine 55 (6), 110-117, 2017 | 646 | 2017 |
Wireless network intelligence at the edge J Park, S Samarakoon, M Bennis, M Debbah Proceedings of the IEEE 107 (11), 2204-2239, 2019 | 633 | 2019 |
Toward low-latency and ultra-reliable virtual reality MS Elbamby, C Perfecto, M Bennis, K Doppler IEEE network 32 (2), 78-84, 2018 | 621 | 2018 |
Matching theory for future wireless networks: Fundamentals and applications Y Gu, W Saad, M Bennis, M Debbah, Z Han IEEE Communications Magazine 53 (5), 52-59, 2015 | 583 | 2015 |
Distributed federated learning for ultra-reliable low-latency vehicular communications S Samarakoon, M Bennis, W Saad, M Debbah IEEE Transactions on Communications 68 (2), 1146-1159, 2019 | 454 | 2019 |
Distributed learning in wireless networks: Recent progress and future challenges M Chen, D Gündüz, K Huang, W Saad, M Bennis, AV Feljan, HV Poor IEEE Journal on Selected Areas in Communications 39 (12), 3579-3605, 2021 | 437 | 2021 |
Beyond 5G with UAVs: Foundations of a 3D wireless cellular network M Mozaffari, ATZ Kasgari, W Saad, M Bennis, M Debbah IEEE Transactions on Wireless Communications 18 (1), 357-372, 2018 | 433 | 2018 |