Count-then-Permute: A Precision-Free Alternative to Inversion Sampling

Kentarou Sasaki
Kentarou Sasaki

CT-RSA, pp. 264-278, 2018.

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Abstract:

The sampling from a discrete probability distribution on computers is an old problem having a wide variety of applications. The inversion sampling which uses the cumulative probability table is quite popular method for discrete distribution sampling. One drawback of inversion sampling (and most of other generic methods) is that it’s table...More

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