A new optimization framework selects alternates for citizens' assemblies using empirical risk minimization with O(a log n) sample complexity, and the linear-loss variant is robust to dropout-probability errors and beats heuristic methods in experiments.
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Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies
A new optimization framework selects alternates for citizens' assemblies using empirical risk minimization with O(a log n) sample complexity, and the linear-loss variant is robust to dropout-probability errors and beats heuristic methods in experiments.