We study the problem of anonymizing data with quasi-sensitive attributes. Quasi-sensitive attributes are not sensitive by themselves, but certain values or their combinations may ...
Background: Whole genome association studies using highly dense single nucleotide polymorphisms (SNPs) are a set of methods to identify DNA markers associated with variation in a ...
Stephen J. Goodswen, Cedric Gondro, Nathan S. Wats...
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Most learning algorithms for undirected graphical models require complete inference over at least one instance before parameter updates can be made. SampleRank is a rankbased lear...
Sameer Singh, Limin Yao, Sebastian Riedel, Andrew ...
After several years of development, the vision of the Semantic Web is gradually becoming reality. Large data repositories have been created and offer semantic information in a mac...