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Federated learning is a distributed learning method to train a shared model by aggregating the locally-computed gradient updates.
“Extracting and composing robust features with denoising autoencoders,”
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol, · 2008
Earlier work this paper cites.
“Fully homomorphic encryption using ideal lattices,”
Craig Gentry, · 2009
Earlier work this paper cites.
“Using very deep autoencoders for content-based image retrieval,”
Alex Krizhevsky and Geoffrey E. Hinton, · 2011
Earlier work this paper cites.
“1-bit stochastic gradient descent and application to data-parallel distributed training of speech DNNs,”
Frank Seide, Hao Fu, Jasha Droppo, Gang Li, and Dong Yu, · 2014
Earlier work this paper cites.
“Autoencoder for words,”
Cheng-Yuan Liou, Wei-Chen Cheng, Jiun-Wei Liou, and Daw-Ran Liou, · 2014
Earlier work this paper cites.
“Privacy-preserving deep learning,”
Reza Shokri and Vitaly Shmatikov, · 2015
Cited alongside, same era.
“Scalable distributed DNN training using commodity GPU cloud computing,”
Nikko Strom, · 2015
Cited alongside, same era.
“Deep residual learning for image recognition,”
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, · 2015
Cited alongside, same era.
“Federated learning of deep networks using model averaging,”
H. Brendan McMahan, Eider Moore, Daniel Ramage, and Blaise Agüera y Arcas, · 2016
Cited alongside, same era.
“Federated learning: Strategies for improving communication efficiency,”
Jakub Kone c ˘ \breve{c} ný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon, · 2016
Later among the works it cites.
“Terngrad: Ternary gradients to reduce communication in distributed deep learning,”
Wei Wen, Cong Xu, Feng Yan, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li, · 2017
Later among the works it cites.
“Sparse communication for distributed gradient descent,”
Alham Fikri Aji and Kenneth Heafield, · 2017
Later among the works it cites.
“Differentially private federated learning: A client level perspective,”
Robin C. Geyer, Tassilo Klein, and Moin Nabi, · 2017
Later among the works it cites.
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