Nov 10, 2020 · GBUN ensembles the untrained randomly generated neural network that softly distributes data samples to multiple neuron outputs and dramatically reduces the communication costs for distributed learning.

GBUN ensembles the untrained randomly generated neural network that softly distributes data samples to multiple neuron outputs and dramatically reduces the communication costs for distributed learning.

Boosting Untrained (Neural) Network (GBUN). GBUN en-sembles the untrained randomly generated neural networks, and each softly distributes data samples to multiple neu-ron outputs. GBUN reduces a large amount of communica-tion volume to train the base predictors in distributed train-ing. However, neural networks are not suitable for handling

Nov 10, 2020 · Our experiments on multiple public datasets show that GBUN is as good as conventional GBDT in terms of prediction accuracy and much better than it in scaling property for distributed learning.

Nov 10, 2020 · GBUN ensembles the untrained randomly generated neural network that softly distributes data samples to multiple neuron outputs and dramatically reduces the communication costs for distributed learning. To avoid creating huge neural networks for high-dimensional data, we extend Simhash algorithm to mimic forward calculation of the neural network.

The proposal achieves a reduction in the bandwidth blocking probability of at least 86.56% relative to AGBA, 84.60% relative to GBUN and 73.26% relative to UTOPIAN. Published in: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

... algorithm is called Guard Band according to Use of the Network (GBUN). Figure 7 shows the application flowchart of the GBUN algorithm by the control plane to establish a circuit. ... ... also...

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GBUN ensembles the untrained randomly generated neural network that softly distributes data samples to multiple neuron outputs and dramatically reduces the communication costs for distributed learning.