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Scalable Federated Learning for Clients with Different Input Image Sizes
  and Numbers of Output Categories

Scalable Federated Learning for Clients with Different Input Image Sizes and Numbers of Output Categories

15 November 2023
Shuhei Nitta
Taiji Suzuki
Albert Rodríguez Mulet
A. Yaguchi
Ryusuke Hirai
    FedML
ArXivPDFHTML

Papers citing "Scalable Federated Learning for Clients with Different Input Image Sizes and Numbers of Output Categories"

3 / 3 papers shown
Title
FjORD: Fair and Accurate Federated Learning under heterogeneous targets
  with Ordered Dropout
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth
Stefanos Laskaridis
Mario Almeida
Ilias Leondiadis
Stylianos I. Venieris
Nicholas D. Lane
189
268
0
26 Feb 2021
FedBN: Federated Learning on Non-IID Features via Local Batch
  Normalization
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
Xiaoxiao Li
Meirui Jiang
Xiaofei Zhang
Michael Kamp
Qi Dou
OOD
FedML
168
787
0
15 Feb 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,572
0
17 Apr 2017
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