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Miao Xu

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2025

ComRank: Ranking Loss for Multi-Label Complementary Label Learning

This work proposes ComRank, a ranking loss framework for MLCLL, which encourages complementary labels to be ranked lower than non-complementary ones, thereby modeling pairwise label relationships and ensures Bayes consistency under both uniform and biased cases.

Jin Zhu, Yi Gao, Miao Xu et al. · 0 citations

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