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RAID
2004
Springer
14 years 4 months ago
Seurat: A Pointillist Approach to Anomaly Detection
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...
IBPRIA
2003
Springer
14 years 4 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
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 ...
Krzysztof Rzadca, Francesc J. Ferri
MM
2005
ACM
146views Multimedia» more  MM 2005»
14 years 4 months ago
Unsupervised content discovery in composite audio
Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. Motivated by the known limitations of traditional supervised approache...
Rui Cai, Lie Lu, Alan Hanjalic
BMCBI
2011
13 years 6 months ago
Motif-guided sparse decomposition of gene expression data for regulatory module identification
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...
ICIP
2003
IEEE
14 years 4 months ago
Automatically organizing digital photographs using time and content
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...