Distributionally robust learning-to-rank under the Wasserstein metric
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DOI: 10.1371/journal.pone.0283574
Abstract: Despite their satisfactory performance, most existing listwise Learning-To-Rank (LTR) models do not consider the crucial issue of robustness. A data set can be contaminated in various ways, including human error in labeling or annotation, distributional… read more here.
Keywords: distributionally robust; drmrr; learning rank; ltr ... See more keywords