Abstract. This paper proposes a new approach to detecting aggregated anomalous events by correlating host file system changes across space and time. Our approach is based on a key...
Yinglian Xie, Hyang-Ah Kim, David R. O'Hallaron, M...
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. Motivated by the known limitations of traditional supervised approache...
Background: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for e...
Ting Gong, Jianhua Xuan, Li Chen, Rebecca B. Riggi...
We present similarity-based methods to cluster digital photos by time and image content. This approach is general, unsupervised, and makes minimal assumptions regarding the struct...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...