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Graphical models are useful tools for describing structured high-dimensional probability distributions.
Approximating discrete probability distributions with dependence trees
C. Chow and C. Liu · 1968
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Learning graphical models using multiplicative weights
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Optimal structure and parameter learning of Ising models
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Sparse logistic regression learns all discrete pairwise graphical models
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