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CVPR
2007
IEEE
14 years 10 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
ICA
2007
Springer
14 years 2 months ago
Mutual Interdependence Analysis (MIA)
Functional Data Analysis (FDA) is used for datasets that are more meaningfully represented in the functional form. Functional principal component analysis, for instance, is used to...
Heiko Claussen, Justinian Rosca, Robert I. Damper
SDM
2011
SIAM
241views Data Mining» more  SDM 2011»
12 years 11 months ago
A Fast Algorithm for Sparse PCA and a New Sparsity Control Criteria
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
Yunlong He, Renato Monteiro, Haesun Park
IJCV
2008
155views more  IJCV 2008»
13 years 8 months ago
Fast Transformation-Invariant Component Analysis
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey
APNOMS
2006
Springer
13 years 12 months ago
Detecting and Identifying Network Anomalies by Component Analysis
Many research works address detection and identification of network anomalies using traffic analysis. This paper considers large topologies, such as those of an ISP, with traffic a...
Le The Quyen, Marat Zhanikeev, Yoshiaki Tanaka