  In this work we present an overview of statistical learning, followed by a
survey of robust streaming techniques and challenges, culminating in several
rigorous results proving the relationship that we motivate and hint at
throughout the journey. Furthermore, we unify often disjoint theorems in a
shared framework and notation to clarify the deep connections that are
discovered. We hope that by approaching these results from a shared
perspective, already aware of the technical connections that exist, we can
enlighten the study of both fields and perhaps motivate new and previously
unconsidered directions of research.
