To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Pipeline architectures provide a versatile and efficient mechanism for constructing visualizations, and they have been implemented in numerous libraries and applications over the p...
John Biddiscombe, Berk Geveci, Ken Martin, Kenn...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
We present an approach to activity discovery, the unsupervised identification and modeling of human actions embedded in a larger sensor stream. Activity discovery can be seen as ...
David Minnen, Thad Starner, Irfan A. Essa, Charles...
We describe the objectives and organization of the CLEF 2006 ad hoc track and discuss the main characteristics of the tasks offered to test monolingual, bilingual, and multilingual...
Giorgio Maria Di Nunzio, Nicola Ferro, Thomas Mand...