Uniform Random Sampling (URS) is the problem of selecting solutions (models) from a Boolean formula such that each solution gets the same probability of being selected. URS has many applications. In large configurable software systems, one wants an unbiased sample of configurations to look for bugs at an affordable cost [12, 13]. Other applications of URS include deep learning verification (to sample inputs from unknown distributions) [2] and evolutionary algorithms (to initialize the input population) [4].
No takes yet. Share an insight, caveat, or question.
Zeyen et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: