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- W2068598467 abstract "We present a general algorithm for learning the structure of discrete Markov random fields from i.i.d. samples. The algorithm either achieves the same computational complexity or lowers the computational complexity of earlier algorithms for several cases, and provides a new low-computational complexity algorithm for the case of Ising models where the underlying graph is the Erdős-Renyi random graph G ∼ G(p, c over p)." @default.
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- W2068598467 date "2012-03-01" @default.
- W2068598467 modified "2023-09-23" @default.
- W2068598467 title "Learning graph structures in discrete Markov random fields" @default.
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- W2068598467 doi "https://doi.org/10.1109/infcomw.2012.6193494" @default.
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