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local/distributed neural network performance questions
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when matlab trains a large sample size (say with >1M), and a good size nn (say, 400 input features, 500-1000 hidden units on 2 layers, and 2 output classes) on local or distributed nodes:
1) does it use mini-batch during training?
2) how does it decide size of mini-batch size?
3) if I run it on multiple distributed nodes, I assume the mini-batch size can be specified within each data set I specify for each distributed nodes?
Thanks, Hc
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