I think that it gives us an adequate account of generalisation in the limit of infinite data (or, more specifically, in the case where we have enough data to wash out the influence of the inductive bias); this is what my original remark was about. I don’t think classical statistical learning theory gives us an adequate account of generalisation in the setting where the training data is small enough for our inductive bias to still matter, and it only has very limited things to say about out-of-distribution generalisation.
I think that it gives us an adequate account of generalisation in the limit of infinite data (or, more specifically, in the case where we have enough data to wash out the influence of the inductive bias); this is what my original remark was about. I don’t think classical statistical learning theory gives us an adequate account of generalisation in the setting where the training data is small enough for our inductive bias to still matter, and it only has very limited things to say about out-of-distribution generalisation.
I see, thanks!