Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
This chapter tackles the relation between declarative languages and multi-agent systems by following the dictates of the five Ws (and one H) that characterize investigations. The ...
Provenance describes how an object came to be in its present state. Thus, it describes the evolution of the object over time. Prior work on provenance has focussed on databases an...