POMDPs are a popular framework for representing decision making problems that contain uncertainty. The high computational complexity of finding exact solutions to POMDPs has spaw...
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
Knowledge transfer is widely held to be a primary mechanism that enables humans to quickly learn new complex concepts when given only small training sets. In this paper, we apply ...
This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree....
This is the first paper on textual case-based reasoning to employ collective classification, a methodology for simultaneously classifying related cases that has consistently attai...