Research map / Label-efficient and robust learning / Recognition and long-tail
Towards a Pairwise Ranking Model with Orderliness and Monotonicity for Label Enhancement
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Proposes a pairwise ranking model for label enhancement that enforces orderliness and monotonicity to infer label distributions from logical multi-label data.
Problem
Label enhancement must infer label distributions from readily available logical (multi-label) annotations; existing methods exploit label ranking but the abstract text is truncated, so details are limited.
Approach
Uses a pairwise label ranking formulation with orderliness and monotonicity constraints to recover label distributions from logical labels, building on label ranking ideas from label enhancement work.
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