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# Optimal Statistical Hypothesis Testing for Social Choice

*Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI)*, PMLR 124:570-579, 2020.

#### Abstract

We address the following question in this paper: “What are the most robust statistical methods for social choice?” By leveraging the theory of uniformly least favorable distributions in the Neyman-Pearson framework to finite models and randomized tests, we characterize uniformly most powerful (UMP) tests, which is a well-accepted statistical optimality w.r.t. robustness, for testing whether a given alternative is the winner under Mallows’ model and under Condorcet’s model, respectively.