This is a question regarding the specific application of online learning theory in the sense of http://www.mit.edu/~9.520/spring08/Classes/online_learning_2008.pdf
I went through ICML papers for 2017 on online learning, and I can say with confidence that 90% of these papers are theoretical papers and should have most appropriately belonged to a statistics or optimization journal (if weren't for the glorious title of being a Machine Learning researcher).
This field is a mathematician's heaven, but as an engineer, it is hard for me to see how I could use these algorithms in practice. The "applications" that people have came up in this field so far are purely academic and does not clearly show practical real world applications as compared to supervised learning/neural nets for things like optical character recognition, or reinforcement learning for robotics applications. I know the latter works, because there has been much written about them, but I am not convinced that the same is true for online learning algorithms.
For example, all from 2017:
All these papers deal with finding some theoretical bound on the "goodness" of their algorithms, but does not clearly show how it relates to practical real world applications.
I am self studying online learning at the moment, using: http://ocobook.cs.princeton.edu/OCObook.pdf
However, I am quickly becoming disillusioned at the lack of serious utility of this mathematical framework. The examples given in the online convex optimization book are very academic. It is difficult to relate them to real life. Even courses on online learning does not provide examples as to how it can be used. I also have tried to dig up some successful applications based on online algorithms, so far I have failed.
Can someone point to some successful real-life applications/implementations of online learning algorithms?