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Coding for Straggler Mitigation in Federated Learning

Coding for Straggler Mitigation in Federated Learning

30 September 2021
Siddhartha Kumar
Reent Schlegel
E. Rosnes
Alexandre Graell i Amat
    FedML
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Papers citing "Coding for Straggler Mitigation in Federated Learning"

4 / 4 papers shown
Title
Securely Aggregated Coded Matrix Inversion
Securely Aggregated Coded Matrix Inversion
Neophytos Charalambides
Mert Pilanci
Alfred Hero
FedML
15
3
0
09 Jan 2023
Computational Code-Based Privacy in Coded Federated Learning
Computational Code-Based Privacy in Coded Federated Learning
M. Xhemrishi
Alexandre Graell i Amat
E. Rosnes
Antonia Wachter-Zeh
FedML
33
4
0
28 Feb 2022
Linear Convergence in Federated Learning: Tackling Client Heterogeneity
  and Sparse Gradients
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients
A. Mitra
Rayana H. Jaafar
George J. Pappas
Hamed Hassani
FedML
55
157
0
14 Feb 2021
Straggler-Resilient Federated Learning: Leveraging the Interplay Between
  Statistical Accuracy and System Heterogeneity
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity
Amirhossein Reisizadeh
Isidoros Tziotis
Hamed Hassani
Aryan Mokhtari
Ramtin Pedarsani
FedML
172
99
0
28 Dec 2020
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