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SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning
  Design and Training

SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training

4 May 2022
Ahsan Ali
Syed Zawad
Paarijaat Aditya
Istemi Ekin Akkus
Ruichuan Chen
Feng Yan
ArXivPDFHTML

Papers citing "SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training"

4 / 4 papers shown
Title
SPIRT: A Fault-Tolerant and Reliable Peer-to-Peer Serverless ML Training
  Architecture
SPIRT: A Fault-Tolerant and Reliable Peer-to-Peer Serverless ML Training Architecture
Amine Barrak
Mayssa Jaziri
Ranim Trabelsi
Fehmi Jaafar
Fábio Petrillo
44
2
0
25 Sep 2023
Exploring the Impact of Serverless Computing on Peer To Peer Training
  Machine Learning
Exploring the Impact of Serverless Computing on Peer To Peer Training Machine Learning
Amine Barrak
Ranim Trabelsi
Fehmi Jaafar
Fábio Petrillo
22
3
0
25 Sep 2023
Architecting Peer-to-Peer Serverless Distributed Machine Learning
  Training for Improved Fault Tolerance
Architecting Peer-to-Peer Serverless Distributed Machine Learning Training for Improved Fault Tolerance
Amine Barrak
Fábio Petrillo
Fehmi Jaafar
29
2
0
27 Feb 2023
FedLesScan: Mitigating Stragglers in Serverless Federated Learning
FedLesScan: Mitigating Stragglers in Serverless Federated Learning
M. Elzohairy
Mohak Chadha
Anshul Jindal
Andreas Grafberger
Jiatao Gu
Michael Gerndt
Osama Abboud
FedML
26
7
0
10 Nov 2022
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