In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Uncertain data is inherent in a few important applications such as environmental surveillance and mobile object tracking. Top-k queries (also known as ranking queries) are often n...
Proteins crystallization is a commonly used technique for protein analysis and subsequent drug design. It predicts the three-dimensional arrangement of the constituent amino acids...