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KDD
2002
ACM
113views Data Mining» more  KDD 2002»
14 years 5 months ago
Scalable robust covariance and correlation estimates for data mining
Covariance and correlation estimates have important applications in data mining. In the presence of outliers, classical estimates of covariance and correlation matrices are not re...
Fatemah A. Alqallaf, Kjell P. Konis, R. Douglas Ma...
KDD
2004
ACM
118views Data Mining» more  KDD 2004»
14 years 5 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 2 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
ICML
2007
IEEE
14 years 5 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
IPMI
2001
Springer
14 years 5 months ago
Spatio-temporal Covariance Model for Medical Images Sequences: Application to Functional MRI Data
Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in...
Frithjof Kruggel, Habib Benali, Mélanie P&e...