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6 votes

When is multidimensional scaling exact for a graph?

If the double centration [1, 2] matrix of your distance (dissimilarity) matrix is gramian (positive semidefinite, that is, all eigenvalues nonnegative) with rank m, then it perfectly spans Euclidean m-...
ttnphns's user avatar
  • 58.3k
5 votes

When is multidimensional scaling exact for a graph?

It can't be always true, because the embedding must satisfy the triangle inequality and your graph might not. Necessary and sufficient conditions are known, but you aren't going to like them>
Thomas Lumley's user avatar
1 vote

What is the interpretation of outlier-robust principal component analysis?

@cgmil: But suppose then that some observations identified as "outliers" are judged to be in-sample, and should not be modified or excluded. Typically there are many more inliers than ...
krkeane's user avatar
  • 2,210
1 vote

Is the assumption of a diagonal covariance matrix on the latent space in a variational autoencoder in any way restrictive?

You seem to be confusing the prior with the posterior. While it's true that you can use a simple prior, like a standard Gaussian, and still have a decoder neural network that maps it to an arbitrarily ...
algebruh's user avatar
  • 131

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