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Module-based regularization improves Gaussian graphical models when observing noisy data.
Magnus Neuman
Joaquín Calatayud
Viktor Tasselius
Martin Rosvall
Published in:
Appl. Netw. Sci. (2024)
Keyphrases
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noisy data
gaussian graphical models
graphical models
noise tolerant
high dimensional
noise free
learning from noisy data
missing data
input data
training data
linear models
belief propagation
pairwise
decision trees
missing values
knn
similarity measure