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» Representation of Functional Data in Neural Networks
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ESANN
2003
15 years 5 months ago
Locally Linear Embedding versus Isotop
Abstract. Recently, a new method intended to realize conformal mappings has been published. Called Locally Linear Embedding (LLE), this method can map high-dimensional data lying o...
John Aldo Lee, Cédric Archambeau, Michel Ve...
VCBM
2010
14 years 10 months ago
Visual Analysis of Integrated Resting State Functional Brain Connectivity and Anatomy
Resting state functional magnetic resonance imaging (rs-fMRI) is an important modality in the study of the functional architecture of the human brain. The correlation between the ...
Andre F. van Dixhoorn, Bastijn H. Vissers, Luca Fe...
ICANN
2007
Springer
15 years 10 months ago
Sparse and Transformation-Invariant Hierarchical NMF
The hierarchical non-negative matrix factorization (HNMF) is a multilayer generative network for decomposing strictly positive data into strictly positive activations and base vect...
Sven Rebhan, Julian Eggert, Horst-Michael Gro&szli...
ISNN
2007
Springer
15 years 10 months ago
Regularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separ...
Andrzej Cichocki, Rafal Zdunek
JMLR
2006
104views more  JMLR 2006»
15 years 4 months ago
Learning Image Components for Object Recognition
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
Michael W. Spratling