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ICASSP
2008
IEEE
16 years 23 days ago
Contextually adaptive signal representation using conditional principal component analysis
The conventional method of generating a basis that is optimally adapted (in MSE) for representation of an ensemble of signals is Principal Component Analysis (PCA). A more ambitio...
Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou...
GFKL
2007
Springer
139views Data Mining» more  GFKL 2007»
16 years 14 days ago
The Noise Component in Model-based Cluster Analysis
The so-called noise-component has been introduced by Banfield and Raftery (1993) to improve the robustness of cluster analysis based on the normal mixture model. The idea is to ad...
Christian Hennig, Pietro Coretto
ASPLOS
2006
ACM
16 years 8 days ago
A performance counter architecture for computing accurate CPI components
Cycles per Instruction (CPI) stacks break down processor execution time into a baseline CPI plus a number of miss event CPI components. CPI breakdowns can be very helpful in gaini...
Stijn Eyerman, Lieven Eeckhout, Tejas Karkhanis, J...
APPT
2005
Springer
15 years 12 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk
EWMF
2005
Springer
15 years 12 months ago
Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis
Abstract. We show that eigenvector decomposition can be used to extract a term taxonomy from a given collection of text documents. So far, methods based on eigenvector decompositio...
Holger Bast, Georges Dupret, Debapriyo Majumdar, B...