Most paralinguistic analysis tasks are lacking agreed-upon evaluation procedures and comparability, in contrast to more `traditional' disciplines in speech analysis. The INTE...
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
In a typical Genetic Association Study (GAS) several hundreds to millions of genomic variables are measured and tested for association with a given set of a phenotypic variables (...
Modern simulation and measurement methods tend to produce meshfree data sets if modeling of processes or objects with free surfaces or boundaries is desired. In Computational Flui...