Ahmed M. A. Sayed
Ahmed M. A. Sayed
Other namesAhmed M. Abdelmoniem, Ahmed Mohamed Abdelmoniem Sayed, Ahmed Sayed
Associate Professor, QMUL
Verified email at - Homepage
Cited by
Cited by
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
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
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
Compressed communication for distributed deep learning: Survey and quantitative evaluation
H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ..., 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
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
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
REFL: Resource-Efficient Federated Learning
AM Abdelmoniem, AN Sahu, M Canini, SA Fahmy
ACM EuroSys,, 2023
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
DC2: Delay-aware compression control for distributed machine learning
AM Abdelmoniem, M Canini
IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021
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
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
Reconciling Mice and Elephants in Data Center Networks
AM Abdelmoniem, B Bensaou
4th IEEE International Conference on Cloud Networking (CLOUDNET'15), 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
Mitigating incast-TCP congestion in data centers with SDN
AM Abdelmoniem, B Bensaou, AJ Abu
Annals of Telecommunications 73, 263-277, 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
Incast-Aware Switch-Assisted TCP Congestion Control for Data Centers
AM Abdelmoniem, B Bensaou
IEEE Global Communications (GlobeCom) Conference: Next Generation Networking …, 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
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
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
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