This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
Carla Scalarin, Jacques Masse, Jean-Marc Boucher, ...
Standard algorithms for template-based information extraction (IE) require predefined template schemas, and often labeled data, to learn to extract their slot fillers (e.g., an ...
We consider the task of driving a remote control car at high speeds through unstructured outdoor environments. We present an approach in which supervised learning is first used to...
Statistical modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evalua...
Milind R. Naphade, Sankar Basu, John R. Smith, Chi...
Training a good text detector requires a large amount of labeled data, which can be very expensive to obtain. Cotraining has been shown to be a powerful semi-supervised learning t...