We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...
We present a learning algorithm for nominal data. It builds a classifier by adding iteratively a simple patch function that modifies the current classifier. Its main advantage lies...
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Abstract— A disjoint support decomposition (DSD) is a representation of a Boolean function F obtained by composing two or more simpler component functions such that the component...
The discussions about learning management systems and reusable learning objects primarily focus on technical standardization issues. Standards such as SCORM or LTSC-LOM will yield...