We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
In the Linked Open Data cloud one of the largest data sets, comprising of 2.5 billion triples, is derived from the Life Science domain. Yet this represents a small fraction of the ...
Estimation of internal mouse anatomy is required for quantitative bioluminescence or fluorescence tomography. However, only surface range data can be recovered from all-optical s...
Background: Last years' mapping of diverse genomes has generated huge amounts of biological data which are currently dispersed through many databases. Integration of the info...
Francisco J. Lopez, Armando Blanco, Fernando Garci...
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...