This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
To deal with the frequent, foreseeable and variable disconnections that occur in a mobile environment, we introduce a exible, two-level consistency model. Semantically related or ...
A large number of bioinformatics analysis tools available today are processor intensive. Keeping in mind that the amount of biological data to be analyzed is growing steadily, and...