Reconceiving Machine Learning

Machine learning is a cottage industry, not an engineering discipline. Nearly every new problem is solved from scratch. There is no reuse of previous solutions. There is no language to describe problems. Research is technique-oriented rather than problem-oriented.

This lack of modularity and composability limits the field advancing. Reinvention is rife.

My research agenda is to develop a composable basis for machine learning. My detailed plan is partially explained in this formal research proposal. This is now funded and I am looking for a postdoc to work with me, Ralf Herbrich, Ule von Luxburg  and Peter Grünwald on the project. If you are interested in the position, I encourage you to read the proposal, and  my recent papers to get a feel for the sort of thing I am doing. The positions will be formally advertised very soon (early September 2010)

As the proposal says, I want to focus on problems rather than solutions. I recently came across a great quote that sums up my feeling on this:

The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science.

- Albert Einstein

Progress to Date

In order to get a feel for the sort of things done so far, look at these recent publications.