High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learnin...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...