Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
With the increasing amount of data and the need to integrate data from multiple data sources, a challenging issue is to find near duplicate records efficiently. In this paper, we ...
Chuan Xiao, Wei Wang 0011, Xuemin Lin, Jeffrey Xu ...
Correlated or discriminative pattern mining is concerned with finding the highest scoring patterns w.r.t. a correlation measure (such as information gain). By reinterpreting corre...
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...