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The information bottleneck and geometric clustering
[article]
2020
arXiv
pre-print
The information bottleneck (IB) approach to clustering takes a joint distribution P(X,Y) and maps the data X to cluster labels T which retain maximal information about Y (Tishby et al., 1999). This objective results in an algorithm that clusters data points based upon the similarity of their conditional distributions P(Y| X). This is in contrast to classic "geometric clustering" algorithms such as k-means and gaussian mixture models (GMMs) which take a set of observed data points {x_i} _i=1:N
arXiv:1712.09657v2
fatcat:7vz2gpkjiraezjm6ifudn2phhy