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Deep Learning in the Era of Edge Computing: Challenges and Opportunities

Deep Learning in the Era of Edge Computing: Challenges and Opportunities

17 October 2020
Mi Zhang
Faen Zhang
Nicholas D. Lane
Yuanchao Shu
Xiao Zeng
Biyi Fang
Shen Yan
Hui Xu
ArXivPDFHTML

Papers citing "Deep Learning in the Era of Edge Computing: Challenges and Opportunities"

4 / 4 papers shown
Title
Distributed intelligence on the Edge-to-Cloud Continuum: A systematic
  literature review
Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review
Daniel Rosendo
Alexandru Costan
P. Valduriez
Gabriel Antoniu
17
80
0
29 Apr 2022
Federated Learning for Internet of Things: Applications, Challenges, and
  Opportunities
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
Tuo Zhang
Lei Gao
Chaoyang He
Mi Zhang
Bhaskar Krishnamachari
Salman Avestimehr
FedML
19
168
0
15 Nov 2021
FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from
  System Perspective
FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
Huan Zhang
Mi Zhang
Xin Liu
P. Mohapatra
Michael DeLucia
FedML
25
18
0
06 Oct 2021
DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices
DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices
Stephan Patrick Baller
Anshul Jindal
Mohak Chadha
Michael Gerndt
4
71
0
21 Aug 2021
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