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ICML
2007
IEEE
14 years 8 months ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski
WEBI
2001
Springer
13 years 11 months ago
Collaborative Filtering Using Principal Component Analysis and Fuzzy Clustering
: Automated collaborative filtering is a popular technique for reducing information overload. In this paper, we propose a new approach for the collaborative filtering using local...
Katsuhiro Honda, Nobukazu Sugiura, Hidetomo Ichiha...
ICONIP
2007
13 years 8 months ago
Flexible Component Analysis for Sparse, Smooth, Nonnegative Coding or Representation
In the paper, we present a new approach to multi-way Blind Source Separation (BSS) and corresponding 3D tensor factorization that has many potential applications in neuroscience an...
Andrzej Cichocki, Anh Huy Phan, Rafal Zdunek, Liqi...
ICASSP
2008
IEEE
14 years 1 months 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...
APPT
2005
Springer
14 years 29 days 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