We investigate the problem of estimating the proportion vector which maximizes the likelihood of a given sample for a mixture of given densities. We adapt a framework developed for...
David P. Helmbold, Yoram Singer, Robert E. Schapir...
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
We describe an approach to extract attribute-value pairs from product descriptions. This allows us to represent products as sets of such attribute-value pairs to augment product d...
Katharina Probst, Rayid Ghani, Marko Krema, Andrew...
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...