We have a paper that is accepted in Inductive Logic Programming (ILP) 2011:
Predictive Learning in Two-way Datasets, by Beau Piccart, Hendrik Blockheel, Andy Georges and Lieven Eechout.
The abstract of the paper reads as follows:
We introduce a new learning setting, called two-way predictive learning, as a special case of relational learning. We demonstrate that this learning setting has some properties that make an alternative learning approach, which we refer to as transposed learning, possible. We show experimentally that transposed learning can yield better results in multi-target learning settings.
We have used this approach to improve on the results we obtained in out PACT 2006 paper, titled “Performance Prediction based on Inherent Program Similarity”. The full results of that research will be part of a future paper.