We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
We propose novel algorithms for organizing large image and video datasets using both the visual content and the associated sideinformation, such as time, location, authorship, and...
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
The increasing amount of data available about software systems poses new challenges for re- and reverse engineering research, as the proposed approaches need to scale. In this con...
In many Web applications, such as blog classification and newsgroup classification, labeled data are in short supply. It often happens that obtaining labeled data in a new domain ...