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Monte-Carlo Sampling for NP-Hard Maximization Problems in the Framework of Weighted Parsing
[chapter]
2000
Lecture Notes in Computer Science
The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in the framework of weighted parsing, and (2) to show how such sampling techniques can be efficiently implemented with an explicit control of the error probability. We provide an algorithm to compute the local sampling probability distribution that guarantee that the global sampling probability indeed corresponds to the aimed
doi:10.1007/3-540-45154-4_10
fatcat:f224t6jmb5cjbcaskxern6dci4