Thank you for the link. Interesting, they used the graph resampling and r-tree approaches already in use for certain kinds of machine learning. (Esp. approximate eigenvalue based classifiers)
Very well written too. Unfortunately the approach described only works for dense countable data that is linearly separable (eta spectral clusters, in fact even stronger assumption) - which still makes it quite useful as a database index.
Very well written too. Unfortunately the approach described only works for dense countable data that is linearly separable (eta spectral clusters, in fact even stronger assumption) - which still makes it quite useful as a database index.