Web: http://arxiv.org/abs/2206.10722

June 23, 2022, 1:10 a.m. | Shivam Gupta, Eric Price

cs.LG updates on arXiv.org arxiv.org

Uniformity testing is one of the most well-studied problems in property
testing, with many known test statistics, including ones based on counting
collisions, singletons, and the empirical TV distance. It is known that the
optimal sample complexity to distinguish the uniform distribution on $m$
elements from any $\epsilon$-far distribution with $1-\delta$ probability is $n
= \Theta\left(\frac{\sqrt{m \log (1/\delta)}}{\epsilon^2} + \frac{\log
(1/\delta)}{\epsilon^2}\right)$, which is achieved by the empirical TV tester.
Yet in simulation, these theoretical analyses are misleading: in many cases, …

arxiv ml testing

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY