We present an approximation scheme for optimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. Thi...
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Soon, much of the data exchanged over the Internet will be encoded in XML, allowing for sophisticated filtering and content-based routing. We have built a filtering engine called ...
Yanlei Diao, Peter M. Fischer, Michael J. Franklin...
Background: Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and...