On the discrepancy between the theoretical analysis and practical implementations of compressed communication for distributed deep learning A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3817-3824, 2020 | 93 | 2020 |
AI-based fog and edge computing: A systematic review, taxonomy and future directions S Iftikhar, SS Gill, C Song, M Xu, MS Aslanpour, AN Toosi, J Du, H Wu, ... Internet of Things 21, 100674, 2023 | 90 | 2023 |
Grace: A compressed communication framework for distributed machine learning H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... 2021 IEEE 41st international conference on distributed computing systems …, 2021 | 83 | 2021 |
Compressed communication for distributed deep learning: Survey and quantitative evaluation H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... http://hdl.handle.net/10754/662495, 2020 | 76 | 2020 |
An efficient statistical-based gradient compression technique for distributed training systems A M Abdelmoniem, A Elzanaty, MS Alouini, M Canini Proceedings of Machine Learning and Systems 3, 297-322, 2021 | 67 | 2021 |
Towards mitigating device heterogeneity in federated learning via adaptive model quantization AM Abdelmoniem, M Canini Proceedings of the 1st Workshop on Machine Learning and Systems, 96-103, 2021 | 58 | 2021 |
REFL: Resource-Efficient Federated Learning AM Abdelmoniem, AN Sahu, M Canini, SA Fahmy ACM EuroSys, https://dl.acm.org/doi/abs/10.1145/35523, 2023 | 48 | 2023 |
Rethinking gradient sparsification as total error minimization A Sahu, A Dutta, A M Abdelmoniem, T Banerjee, M Canini, P Kalnis Advances in Neural Information Processing Systems 34, 8133-8146, 2021 | 48 | 2021 |
Ant colony and load balancing optimizations for AODV routing protocol AM Abd Elmoniem, HM Ibrahim, MH Mohamed, AR Hedar International Journal of Sensor Networks and Data Communications 1, 1-14, 2011 | 47 | 2011 |
A comprehensive empirical study of heterogeneity in federated learning AM Abdelmoniem, CY Ho, P Papageorgiou, M Canini IEEE Internet of Things Journal 10 (16), 14071-14083, 2023 | 36* | 2023 |
DC2: Delay-aware compression control for distributed machine learning AM Abdelmoniem, M Canini IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021 | 35 | 2021 |
SICC: SDN-based incast congestion control for data centers AM Abdelmoniem, B Bensaou, AJ Abu 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 35 | 2017 |
Reconciling Mice and Elephants in Data Center Networks AM Abdelmoniem, B Bensaou 4th IEEE International Conference on Cloud Networking (CLOUDNET'15), 2015 | 34 | 2015 |
Empirical analysis of federated learning in heterogeneous environments AM Abdelmoniem, CY Ho, P Papageorgiou, M Canini Proceedings of the 2nd European Workshop on Machine Learning and Systems, 1-9, 2022 | 33 | 2022 |
Mitigating incast-TCP congestion in data centers with SDN AM Abdelmoniem, B Bensaou, AJ Abu Annals of Telecommunications 73, 263-277, 2018 | 31* | 2018 |
Efficient Switch-Assisted Congestion Control for Data Centers: an Implementation and Evaluation AM Abdelmoniem, B Bensaou 34rd IEEE International Performance Computing and Communications Conference …, 2015 | 31* | 2015 |
Incast-Aware Switch-Assisted TCP Congestion Control for Data Centers AM Abdelmoniem, B Bensaou IEEE Global Communications (GlobeCom) Conference: Next Generation Networking …, 2015 | 31 | 2015 |
An ant colony optimization algorithm for the mobile ad hoc network routing problem based on AODV protocol AM Abdel-Moniem, MH Mohamed, AR Hedar 2010 10th International Conference on Intelligent Systems Design and …, 2010 | 30 | 2010 |
Hysteresis-based active queue management for TCP traffic in data centers AM Abdelmoniem, B Bensaou IEEE INFOCOM 2019-IEEE Conference on Computer Communications, 1621-1629, 2019 | 29 | 2019 |
Huffman coding based encoding techniques for fast distributed deep learning RR Gajjala, S Banchhor, AM Abdelmoniem, A Dutta, M Canini, P Kalnis Proceedings of the 1st Workshop on Distributed Machine Learning, 21-27, 2020 | 28 | 2020 |