Model-based machine learning + Edward


#1

The upcoming book Model-Based Machine Learning by John Winn and Chris Bishop presents machine learning in a model based, probabilistic framework.

The book contains in detail several examples (skill ranking, email filtering, time series modeling) in a Bayesian probabilistic framework.

All the examples are solved using message passing or belief propagation inference with Infer.NET

Could this be done with Edward? I think it would be very strong to extend the examples folder following the MBML book.

Your thoughts?


#2

As with many things, it only requires someone to put in the time. It’s certainly possible with our current algorithms. That said, Kevin Murphy is preparing a new version of his textbook and is using Edward; Dave Blei is preparing a graphical model textbook (not released in a few years) that also uses Edward. It would be nice if someone (either Chris Bishop or any enthusiastic Edward user) to convert the examples.