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
REFL: Resource-Efficient Federated Learning
AM Abdelmoniem, AN Sahu, M Canini, SA Fahmy
ACM EuroSys,, 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
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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