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$\begingroup$ How do you know it's a "batch-method"? Also, when does it do a forward/backwards optim then? After all the observations? So if I have 1000 observations, first backwards-prop is after all 1000 observations are fed through? $\endgroup$
– user1357015
Commented May 30, 2016 at 14:35
$\begingroup$ Just read the first part of the paper :-) This part answers your questions. Hints: Batch methods, such as Limited memory BFGS + A weakness of batch L-BFGS and CG, which require the computation of the gradient on the entire dataset to make an update, is that they do not scale gracefully with the number of examples $\endgroup$
– sascha
Commented May 30, 2016 at 14:36

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