We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
The main objective of machine discovery is the determination of relations between data and of data models. In the paper we describe a method for discovery of data models represent...
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
We present parallel algorithms for building decision-tree classifiers on shared-memory multiprocessor (SMP) systems. The proposed algorithms span the gamut of data and task parall...
Mohammed Javeed Zaki, Ching-Tien Ho, Rakesh Agrawa...
CoIL challenge 2000 was a supervised learning contest that attracted 43 entries. The authors of 29 entries later wrote explanations of their work. This paper discusses these repor...