Prati
Atal Narayan Sahu
Atal Narayan Sahu
Data Scientist, Regology
Potvrđena adresa e-pošte na regology.com
Naslov
Citirano
Citirano
Godina
Natural compression for distributed deep learning
S Horvóth, CY Ho, L Horvath, AN Sahu, M Canini, P Richtárik
Mathematical and Scientific Machine Learning, 129-141, 2022
1452022
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
852020
Efficient sparse collective communication and its application to accelerate distributed deep learning
J Fei, CY Ho, AN Sahu, M Canini, A Sapio
Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 676-691, 2021
682021
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
382021
REFL: Resource-Efficient Federated Learning
AM Abdelmoniem, AN Sahu, M Canini, SA Fahmy
212023
Resource-Efficient Federated Learning
AM Abdelmoniem, AN Sahu, M Canini, SA Fahmy
arXiv preprint arXiv:2111.01108, 2021
21*2021
On the convergence analysis of asynchronous SGD for solving consistent linear systems
AN Sahu, A Dutta, A Tiwari, P Richtárik
Linear Algebra and its Applications 663, 1-31, 2023
52023
Rethinking gradient sparsification as total error minimization
A Narayan Sahu, A Dutta, AM Abdelmoniem, T Banerjee, M Canini, ...
arXiv e-prints, arXiv: 2108.00951, 2021
2021
Published work in the proceedings of AAAI 2020 The Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep …
CY Ho, AN Sahu, M Canini, P Kalnis
2020
On the Convergence Analysis of Asynchronous SGD for Solving Consistent Linear Systems
A Narayan Sahu, A Dutta, A Tiwari, P Richtárik
arXiv e-prints, arXiv: 2004.02163, 2020
2020
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
CY Ho, AN Sahu, M Canini, P Kalnis
2020
sands-lab/layer-wise-aaai20: Code repository for AAAI'20 paper: On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication …
A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ...
Github, 2019
2019
IntML: Natural Compression for Distributed Deep Learning
S Horváth, CY Ho, L Horváth, AN Sahu, M Canini, P Richtárik
Training 1 (2), 3, 0
Rethinking gradient sparsification as total error minimization Download PDF
AN Sahu, A Dutta, AM Abdelmoniem, T Banerjee, M Canini, P Kalnis
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