Editing Discrepancy theory (section)

== Applications ==
Applications for discrepancy theory include:
* Numerical integration: [[Monte Carlo method]]s in high dimensions
* Computational geometry: [[Divide-and-conquer algorithm]]
* Image processing: [[Halftone|Halftoning]]
* Random trial formulation: [[Randomized controlled trial]]<ref>{{cite journal|last=Harshaw|first=Christopher| author2=Sävje, Fredrik | author3= Spielman, Daniel A | author4 = Zhang, Peng | title=Balancing covariates in randomized experiments with the Gram--Schmidt walk design | journal=Journal of the American Statistical Association | pages=2934–2946 | year=2024 |volume=119 |issue=548 |doi=10.1080/01621459.2023.2285474 | url= https://www.tandfonline.com/doi/full/10.1080/01621459.2023.2285474| arxiv=1911.03071 }}</ref> <ref>{{cite video|last1=Spielman|first1=Daniel|date=11 May 2020|title= Using discrepancy theory to improve the design of randomized controlled trials|url= https://www.ias.edu/video/csdm/2020/0511-DanielSpielman}}</ref> <ref>{{cite video|last1=Spielman|first1=Daniel|date=29 January 2021|title= Discrepancy Theory and Randomized Controlled Trials|url= https://www.youtube.com/watch?v=ZMRAeq-7hHU}}</ref>