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Split Learning (SL) is a new collaborative learning technique that allows participants, e.g.
The impact of the mit-bih arrhythmia database
G. B. Moody and R. G. Mark · 2001
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Homomorphic encryption for arithmetic of approximate numbers
J. H. Cheon, A. Kim, M. Kim, and Y. Song · 2017
Earlier work this paper cites.
Distributed learning of deep neural network over multiple agents
O. Gupta and R. Raskar · 2018
Earlier work this paper cites.
Split learning for health: Distributed deep learning without sharing raw patient data
P. Vepakomma, O. Gupta, T. Swedish, and R. Raskar · 2018
Cited alongside, same era.
Detailed comparison of communication efficiency of split learning and federated learning
A. Singh, P. Vepakomma, O. Gupta, and R. Raskar · 2019
Cited alongside, same era.
Reducing leakage in distributed deep learning for sensitive health data
P. Vepakomma, O. Gupta, A. Dubey, and R. Raskar · 2019
Cited alongside, same era.
Federated learning
Q. Yang, Y. Liu, Y. Cheng, Y. Kang, T. Chen, and H. Yu · 2019
Later among the works it cites.
Can we use split learning on 1d cnn models for privacy preserving training?
S. Abuadbba, K. Kim, M. Kim, C. Thapa, S. A. Camtepe, Y. Gao, H. Kim, and S. Nepal · 2020
Later among the works it cites.
The Road to Conscious Machines: The Story of AI
M. Wooldridge · 2020
Later among the works it cites.
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