Introduction
There is an abundance of diverse problems in Science. Most of these problems identify with a specific domain, and researchers of this domain work on this problem in isolation from other domains. Machine Learning, in particular is one of the domains where research has been advancing at an unprecedented pace; plus, many of these recent discoveries can potentially solve a whole class of important problems across many domains. The key reasons for the lack of cross pollination of new ideas in Machine Learning is first that the community of Machine Learning researchers are not exposed to the important problems of other domains; secondly, the community of researchers in other domains find it hard to catch up with the research in Machine Learning.