CISE: Common and Individual Structure Explained for Multiple Graphs
Specific dimension reduction methods for replicated graphs
(multiple undirected graphs repeatedly measured on a common set of
nodes). The package contains efficient procedures for estimating
a shared baseline propensity matrix and graph-specific low rank
matrices. The algorithm uses block coordinate descent algorithm to
solve the model, which alternatively performs L2-penalized logistic
regression and multiple partial eigenvalue decompositions, as described
in the paper Wang et al. (2017) <arXiv:1707.06360>.
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