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Kris Villez

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Purdue University

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14 Dec 2014 Truncated multivariate normal Generates pseudo-random vectors drawn from the truncated multivariate normal distribution. Author: Tim Benham

Hi,

I just tested and used this package. I noticed that the Gibbs sampler does not necessarily start in a feasible point (within the polygon). For large-dimensional problems, this can make the chance of arriving in the feasible space by random sampling extremely low.

I made a small modification to the code by using the constrained maximum likelihood solution as the first sample. This helps to avoid this situation.

Otherwise, I think this is a great piece of code. Thanks for sharing.

Best,
Kris

04 Apr 2013 Kernel PCA and Pre-Image Reconstruction standard PCA, Gaussian kernel PCA, polynomial kernel PCA, pre-image reconstruction Author: Quan Wang

Dear Quan Wang,

Thanks for sharing your code. However, I am not able to reproduce the results displayed in Figure 3 and 4 of your paper.

For Figure 3, it is not clear what the order of the applied polynomial is.

For Figure 4, the two features are highly correlated while the should in fact be uncorrelated. I wondered if this is a mistake in the paper or in the code.

Thanks for your comments,
Kris

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