: We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centres are automatically derived by mode seeking wit...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
There has been considerable past work studying data integration and uncertain data in isolation. We develop the foundations for local-as-view (LAV) data integration when the sourc...
Parag Agrawal, Anish Das Sarma, Jeffrey D. Ullman,...