Primarily, we treatment about NN generalization on difficulties exactly where the enter House is constant, frequently R^n. Â The authors argue that the finite-set results are related to these complications, for the reason that one can always discretize R^n to obtain a finite established. Â I don't Assume this captures the kinds of operate complexity we care about for NNs.
One way that SGD could differ from random sampling is the fact SGD will typically only get to the boundary of the region with zero instruction error, Whilst random sampling will sample uniformly within the area.
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I believe this makes sense for clarifying the estimate, as this Section of the put up explains the relatively typical arguments that neural networks generalize pretty well, are not really confined with regard to input/output relations, yet most input/output relations is not going to generalize correctly to new info. So there should be something much more right here.
There are different priors around functions for which we are able to work out the precise posterior. (E.g., Gaussian processes.) Having said that, carrying out Bayesian inference on these priors would not complete as well as neural networks on most datasets. So realizing SGD is Bayesian is simply intriguing if we also are aware that the prior is attention-grabbing.
 Any time you take out the metric, They are similar.  So you've minimal electricity to predict what the speed-distortion principle notion of complexity is going to say, when you finally place the metric again in.
Largely, we care about NN generalization on troubles the place the input Room is constant, normally R^n.  The authors argue the finite-established results are relevant to those problems, because one can always discretize R^n to get a finite set.  I do not think this captures the kinds of purpose complexity we treatment 파워볼 about for NNs.
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Falsifiable Hypothesis: Compare SGD with overtaining on the random sampling algorithm. You will see that features which have been not likely to get created by random sampling will likely be additional likely under SGD with overtraining.
 But the example exhibits that the assert about complexity steps will only keep if our translation is "ok" in some sense.  If We have no strategy 파워볼 what "ok" signifies, a little something is lacking with the story.)
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