* Estimators for [Baeysian and Deep learning] approaches usually have to solve intractable optimization problems. Thus, they fall back on approximations and get stuck in local maxima, and you don&#x27;t really know what you&#x27;re getting. *<p>So, with deep nets, how big a problem is getting stuck in local optima?<p>I mean, my intuition is that it&#x27;s not magic, you&#x27;re optimising a system of functions so you&#x27;d get stuck in local optima in the same way you get stuck with a single function. Is that generally the case?