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COSMITS
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dengemann committed Oct 25, 2013
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in recovering the size of the low rank subspace. The likelihood with PCA
is higher than FA in this case. However PCA fails and overestimates
the rank when heteroscedastic noise is present. Under appropriate
circumstances the low rank models are more likily than shrinkage models.
circumstances the low rank models are more likely than shrinkage models.
The automatic estimation from
Automatic Choice of Dimensionality for PCA. NIPS 2000: 598-604
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