Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...
Ji Zhang, Qigang Gao, Hai H. Wang, Qing Liu, Kai X...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...