Tournaments for Selecting the Best Under Adversarial Errors
نویسندگان
چکیده
We present a family of adaptive pairwise tournaments which are provably robust against large error fractions when used to determine the largest element in a set. These tournaments use nk pairwise comparisons but have only O(k + log n) depth where n is the number of players and k is a robustness parameter (for reasonable values of n and k). We show how these tournaments can be used to prove multiclass-to-binary reductions in machine learning with the tightest ever analysis.
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