> Minor assumption failures can suddenly matter alot. Indeed. In fact this is nowadays painfully obvious in Fisher's maximum-likelihood based estimators -- the

> Minor assumption failures can suddenly matter alot. Indeed. In fact this is nowadays painfully obvious in Fisher's maximum-likelihood based estimators -- they do not have nice 'continuity' properties that will give a graceful degradation. We figured out how to deal with this once the problem was recognized. However, we see the same problem raising its head in some of the deep neural net literature. Tiny variations often does not cause tiny distortions in the output -- thats cause for some legitimate concern.