In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
The purpose of the study was to determine public university South Dakota (USA) distance faculty perceptions regarding intended level of learning objectives for four selected modes...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...