FedMax: Enabling a Highly-Efficient Federated Learning Framework
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Hongkai Xiong | Jin Li | Haohang Xu | Hui Lu | H. Xiong | Haohang Xu | Hui Lu | Jin Li
[1] Ian Goodfellow,et al. Deep Learning with Differential Privacy , 2016, CCS.
[2] Alexander Aiken,et al. Legion: Expressing locality and independence with logical regions , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.
[3] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[4] Yann LeCun,et al. Deep learning with Elastic Averaging SGD , 2014, NIPS.
[5] Sarvar Patel,et al. Practical Secure Aggregation for Privacy-Preserving Machine Learning , 2017, IACR Cryptol. ePrint Arch..
[6] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[7] Randy H. Katz,et al. Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center , 2011, NSDI.
[8] Zheng Zhang,et al. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.
[9] Carlos Guestrin,et al. Distributed GraphLab : A Framework for Machine Learning and Data Mining in the Cloud , 2012 .
[10] P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .
[11] Bernd Mohr,et al. Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis , 2017 .
[12] Scott Shenker,et al. Fast and Interactive Analytics over Hadoop Data with Spark , 2012, login Usenix Mag..
[13] Michael I. Jordan,et al. Advances in Neural Information Processing Systems 30 , 1995 .
[14] Alexander J. Smola,et al. Scaling Distributed Machine Learning with the Parameter Server , 2014, OSDI.
[15] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[16] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[17] Weisong Shi,et al. Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.
[18] Alexander J. Smola,et al. On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants , 2015, NIPS.
[19] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[20] Ji Liu,et al. Staleness-Aware Async-SGD for Distributed Deep Learning , 2015, IJCAI.
[21] Christoforos E. Kozyrakis,et al. TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory , 2017, ASPLOS.
[22] James T. Kwok,et al. Asynchronous Distributed ADMM for Consensus Optimization , 2014, ICML.
[23] Blaise Agüera y Arcas,et al. Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.
[24] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[25] Marc'Aurelio Ranzato,et al. Building high-level features using large scale unsupervised learning , 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[26] Richard Mortier,et al. Probabilistic Synchronous Parallel , 2017, ArXiv.