Sampling Exactly from the Normal Distribution
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Publication:2828164
DOI10.1145/2710016zbMath1357.65008arXiv1303.6257OpenAlexW1847048756WikidataQ56057952 ScholiaQ56057952MaRDI QIDQ2828164
Publication date: 24 October 2016
Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1303.6257
Sampling theory, sample surveys (62D05) Monte Carlo methods (65C05) Random number generation in numerical analysis (65C10)
Related Items (13)
The expected bit complexity of the von Neumann rejection algorithm ⋮ Isochronous Gaussian Sampling: From Inception to Implementation ⋮ COSAC: COmpact and Scalable Arbitrary-Centered Discrete Gaussian Sampling over Integers ⋮ Homomorphic Encryption Standard ⋮ An improved exact sampling algorithm for the standard normal distribution ⋮ Secure random sampling in differential privacy ⋮ Faster Gaussian sampling for trapdoor lattices with arbitrary modulus ⋮ Sampling from Arbitrary Centered Discrete Gaussians for Lattice-Based Cryptography ⋮ How to sample a discrete Gaussian (and more) from a random oracle ⋮ Exact sublinear binomial sampling ⋮ Sampling from discrete Gaussians for lattice-based cryptography on a constrained device ⋮ On the rejection rate of exact sampling algorithm for discrete Gaussian distributions over the integers ⋮ Implementation of lattice trapdoors on modules and applications
Uses Software
Cites Work
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- Extensions of von Neumann's Method for Generating Random Variables
- Mersenne twister
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- Von Neumann's Comparison Method for Random Sampling from the Normal and Other Distributions
- Extensions of Forsythe's Method for Random Sampling from the Normal Distribution
- On Buffon Machines and Numbers
- On lattices, learning with errors, random linear codes, and cryptography
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