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Complexity of approximating bounded variants of optimization problems

✍ Scribed by Miroslav Chlebík; Janka Chlebíková

Book ID
108281153
Publisher
Elsevier Science
Year
2006
Tongue
English
Weight
354 KB
Volume
354
Category
Article
ISSN
0304-3975

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Probabilistic inference and maximum a posteriori (MAP) explanation are two important and related problems on Bayesian belief networks. Both problems are known to be NP-hard for both approximation and exact solution. In 1997, Dagum and Luby showed that efficiently approximating probabilistic inferenc