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Recently, I have been working on RNNs (LSTM specifically) to do time series prediction and I have used different frameworks such as deeplearning4j and theano (keras). As you may know, one of the hyperparameters of the model is batch_size which has an effect on the model accuracy. I found this paper which suggests that by using online learning instead of batch learning, the convergence can be reached significantly faster using on-line training than batch training, with no apparent difference in accuracy. Now I have the following questions:

  1. How can we do online learning in any of those models? Does it basically mean to set the batch_size to 1?
  2. Any ideas and thoughts about this? Is online learning really helpful?

It is worth to mention that I am trying to do time series analysis on streaming data and that is why I thought online learning might be useful in my case.

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How can we do online learning in any of those models? Does it basically mean to set the batch_size to 1?

yes

Any ideas and thoughts about this? Is online learning really helpful?

see Tradeoff batch size vs. number of iterations to train a neural network

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  • $\begingroup$ It is a great question and I'm wondering what you think about the answer? Did you find that useful? $\endgroup$
    – ahajib
    Commented Jul 15, 2016 at 14:01

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