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With the increasing scale of machine learning tasks, it has become essential to reduce the communication between computing nodes.
S. Shi, Q. Wang, K. Zhao, Z. Tang, Y. Wang, X. Huang, and X. Chu · 1901
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M. G. Rabbat and R. D. Nowak · 2005
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An asynchronous mini-batch algorithm for regularized stochastic optimization
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Gradient sparsification for communication-efficient distributed optimization
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W. Wen, C. Xu, F. Yan, C. Wu, Y. Wang, Y. Chen, and H. Li · 2017
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The convergence of sparsified gradient methods
D. Alistarh, T. Hoefler, M. Johansson, N. Konstantinov, S. Khirirat, and C. Renggli · 2018
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Distributed learning with compressed gradients
S. Khirirat, H. R. Feyzmahdavian, and M. Johansson
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A convergence analysis of distributed sgd with communication-efficient gradient sparsification
S. Shi, K. Zhao, Q. Wang, Z. Tang, and X. Chu · 2019
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