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 ...
We introduce Scioto, Shared Collections of Task Objects, a lightweight framework for providing task management on distributed memory machines under one-sided and globalview parall...
James Dinan, Sriram Krishnamoorthy, D. Brian Larki...
We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
Abstract. In this paper, we propose a novel classification algorithm, called geometrical probability covering (GPC) algorithm, to improve classification ability. On the basis of ...
Abstract. In this paper, we explore the syntactic relation patterns for opendomain factoid question answering. We propose a pattern extraction method to extract the various relatio...