Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
This paper deals with automatically learning the spatial distribution of a set of images. That is, given a sequence of images acquired from well-separated locations, how can they ...
1 The purpose of this study is to evaluate the validity of measuring grammatical diversity with a specifically designed Lexical Diversity Assessment Tool (LDAT). A secondary object...
Scott Leigh Healy, Joseph D. Weintraub, Philip M. ...
We present an evaluation of four knowledge base systems with respect to use in large Semantic Web applications. We discuss the performance of each system. In particular, we show t...