We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
A Data Warehouse DW is a database that collects and stores data from multiple remote and heterogeneous information sources. When a query is posed, it is evaluated locally, without...
We consider the problem of wide-area large-scale text search over a peer-to-peer infrastructure. A wide-area search infrastructure with billions of documents and millions of searc...
Vijay Gopalakrishnan, Bobby Bhattacharjee, Peter J...
This paper proposes a novel model-guided segmentation framework utilizing a statistical surface wavelet model as a shape prior. In the model building process, a set of training sh...
Yang Li, Tiow Seng Tan, Ihar Volkau, Wieslaw L. No...