On the Error of Random Sampling: Uniformly Distributed Random Points on Parametric Curves

Loading...
Thumbnail Image

Identifiers

Publication date

Defense date

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Given a parametric polynomial curve γ:[a,b] →Rn, how can we sample a random point x ∈ im(γ) in such a way that it is distributed uniformly with respect to the arc-length? Unfortunately, we cannot sample exactly such a point—even assuming we can perform exact arithmetic operations. So we end up with the following question: how does the method we choose affect the quality of the approximate sample we obtain? In practice, there are many answers. However, in theory, there are still gaps in our understanding. In this paper, we address this question from the point of view of complexity theory, providing bounds in terms of the size of the desired error.

Description

This is the accepted version of the conference paper published by ACM in ISSAC '22: International Symposium on Symbolic and Algebraic Computation. The Version of Record is available at https://doi.org/10.1145/3476446.3536190.

Keywords

Bibliographic citation

Chalkis, A., Katsamaki, C., & Tonelli-Cueto, J. (2022). On the Error of Random Sampling: Uniformly Distributed Random Points on Parametric Curves. In ISSAC '22: Proceedings of the 2022 International Symposium on Symbolic and Algebraic Computation (pp. 273–282). Association for Computing Machinery.

Collections

Endorsement

Review

Supplemented By

Referenced By