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» An extension of the ICA model using latent variables
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GRC
2010
IEEE
13 years 9 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
CVPR
2012
IEEE
11 years 11 months ago
Image categorization using Fisher kernels of non-iid image models
The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...
NIPS
2007
13 years 10 months ago
Convex Relaxations of Latent Variable Training
We investigate a new, convex relaxation of an expectation-maximization (EM) variant that approximates a standard objective while eliminating local minima. First, a cautionary resu...
Yuhong Guo, Dale Schuurmans
ICASSP
2010
IEEE
13 years 9 months ago
On the robustness of the multidimensional state coherence transform for solving the permutation problem of frequency-domain ICA
A common problem in frequency domain independent component analysis (ICA) is the so called permutation problem which arises due to the independent demixing in each frequency bin. ...
Benedikt Loesch, Francesco Nesta, Bin Yang
BMCBI
2006
203views more  BMCBI 2006»
13 years 8 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...