We present new training methods that aim to mitigate local optima and slow convergence in unsupervised training by using additional imperfect objectives. In its simplest form, lat...
Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jura...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
—For the description of reactive systems, there is a large number of languages and formalisms, and depending on a particular application or design phase, one of them may be bette...
Jens Brandt, Mike Gemunde, Klaus Schneider, Sandee...
We present a text-based approach for the automatic indexing and retrieval of digital photographs taken at crime scenes. Our research prototype, SOCIS, goes beyond keyword-based ap...
In a text categorization task, classification on some hierarchy of classes shows better results than the case without the hierarchy. In current environments where large amount of ...