Fetching the paper…
Reading the bibliography…
Federated Learning enables visual models to be trained in a privacy-preserving way using real-world data from mobile devices.
Gradient methods for minimizing composite objective function
Yu Nesterov · 2007
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
EMNIST: an extension of MNIST to handwritten letters
Gregory Cohen, Saeed Afshar, Jonathan Tapson, and André van Schaik · 2017
Earlier work this paper cites.
Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
Earlier work this paper cites.
Leaf: A benchmark for federated settings
Sebastian Caldas, Peter Wu, Tian Li, Jakub Konečnỳ, H Brendan McMahan, Virginia Smith, and Ameet Talwalkar · 2018
Cited alongside, same era.
On the convergence of federated optimization in heterogeneous networks
Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, and Virginia Smith · 2018
Cited alongside, same era.
Measuring the effects of data parallelism on neural network training
Christopher J Shallue, Jaehoon Lee, Joe Antognini, Jascha Sohl-Dickstein, Roy Frostig, and George E Dahl · 2018
Cited alongside, same era.
Federated learning with non-IID data
Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, and Vikas Chandra · 2018
Cited alongside, same era.
Advanced convolutional neural networks
TensorFlow
Cited in the paper.
On the convergence of FedAvg on non-IID data
Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, and Zhihua Zhang · 2019
Closest in time.
Robust and communication-efficient federated learning from non-IID data
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, and Wojciech Samek · 2019
Closest in time.
Bayesian nonparametric federated learning of neural networks
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, and Yasaman Khazaeni · 2019
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…