Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio c...
Douglas Turnbull, Luke Barrington, D. Torres, Gert...
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
The goal of this work is to contribute to the field of interoperability of Workflow models. To achieve this interoperability, we have built a generic architecture that s three lev...
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...