Optimal choice: new machine learning problem and its solution
  The task of learning to pick a single preferred example out a finite set of
examples, an "optimal choice problem", is a supervised machine learning problem
with complex, structured input. Problems of optimal choice emerge often in
various practical applications. We formalize the problem, show that it does not
satisfy the assumptions of statistical learning theory, yet it can be solved
efficiently in some cases. We propose two approaches to solve the problem. Both
of them reach good solutions on real life data from a signal processing
application.
