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In this paper, we propose a communication-efficient model of sparse bidirectional neural network to intelligently process distributed data. The basic idea of the proposal is a modified bidirectional communication between the core and the edge of Internet by model parameters. The formulation and the procedures of the proposal are investigated. In theory, we prove that the proposed neural network is...
In this paper, we propose a novel pruning model of deep learning for large-scale distributed data processing to simulate a potential application in the geographical neighbor of Internet of Things. We formulate a general model of pruning learning, and we investigate the procedure of pruning learning to satisfy hard constraint and soft constraint. The hard constraint is a class of non-flexible setting...
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