Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
The objective of this paper is classifying images by the object categories they contain, for example motorbikes or dolphins. There are three areas of novelty. First, we introduce ...
Abstract. The goal of the APOSDLE (Advanced Process-Oriented SelfDirected Learning environment) project is to support work-integrated learning of knowledge workers. We argue that w...
Stefanie N. Lindstaedt, Peter Scheir, Armin Ulbric...
Spatial language video retrieval is an important real-world problem that is also a natural test bed for evaluating semantic structures for natural language descriptions of motion ...