The Show, Attend and Tell paper describes a solution to image captioning.
I am wondering: Is this novel machine learning application and instances of (semi-)supervised or unsupervised learning (in the broadest sense)? And if not, why?
My confusion comes from the fact that for disconnect that I'm experiencing, when learning introductory machine learning concepts, where everything is categorized as a (semi-)supervised problem, where the output is either a vector or a label or unsupervised learning problem, where clustering is performed - and the above solution, whose output seems to be a much more complicated object, for example a word.
I guess one could encode words in vectors or labels drawn from a large pools of possible labels, but I'm very doubtful if this is actually how it is done.
The machine learning solutions from the textbooks, that I learned so far, only seem to apply for problems where the output is a number (such as predicting a the income in a country based on years of education and age) or a label (such as in the Iris dataset). But the linked problem seem of a very different category.
(I tried going over the details of the Show, Attend and Tell paper. While I do know a bit of stats, I lacked machine learning knowledge to be able to discern whether their is ultimately a supervised or unsupervised machine learning solution.)