Empirical studies of multitask learning provide some evidence that the performance of a learning system on its intended targets improves by presenting to the learning system relat...
John Case, Sanjay Jain, Matthias Ott, Arun Sharma,...
This paper describes an approach being explored to improve the usefulness of machine learning techniques for generating classification rules for complex, real world data. The appr...
—This paper discusses a new implementation of embodied evolution that uses the concept of punctuated anytime learning to increase the complexity of tasks that the learning system...
A number of Inductive Logic Programming (ILP) systems have addressed the problem of learning First Order Logic (FOL) discriminant definitions by first reformulating the FOL lear...
Machine learning research has been very successful at producing powerful, broadlyapplicable classification learners. However, many practical learning problems do not fit the class...