A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Discovering a junction tree behind a Markov network by a greedy algorithm
Abstract In our paper (Annals of Operations Research, 193:71–90, 2012) we introduced a special kind of k−1-width junction tree, called k-th order cherry tree in order to approximate a joint probability distribution. The approximation is the best if the Kullback–Leibler divergence between the true joint probability distribution and the approximating one is minimal. Finding the best approximating k−1-width junction tree probability distribution is NP-complete if 2
Discovering a junction tree behind a Markov network by a greedy algorithm
Abstract In our paper (Annals of Operations Research, 193:71–90, 2012) we introduced a special kind of k−1-width junction tree, called k-th order cherry tree in order to approximate a joint probability distribution. The approximation is the best if the Kullback–Leibler divergence between the true joint probability distribution and the approximating one is minimal. Finding the best approximating k−1-width junction tree probability distribution is NP-complete if 2
Discovering a junction tree behind a Markov network by a greedy algorithm
Szántai, Tamás (author) / Kovács, Edith (author)
2013
Article (Journal)
English
Discovering a junction tree behind a Markov network by a greedy algorithm
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