Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
Lists of ordered objects are widely used as representational forms. Such ordered objects include Web search results or best-seller lists. Clustering is a useful data analysis tech...
Abstract. In order to exploit the dependencies in relational data to improve predictions, relational classification models often need to make simultaneous statistical judgments abo...
Clustering is a prominent method in the data mining field. It is a discovery process that groups data such that intra cluster similarity is maximized and the inter cluster similar...
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...