First optimal algorithm for fair top-k aggregation and 2-approximation for fair full rank aggregation under Spearman footrule (L1 distance).
Journal of Computer and System Sciences , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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Dataset distillation introduces fairness gaps from subgroup pattern mismatches rather than just imbalance; distilling to a group-agnostic barycenter of predictive information reduces these gaps.
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Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
First optimal algorithm for fair top-k aggregation and 2-approximation for fair full rank aggregation under Spearman footrule (L1 distance).
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Fair Dataset Distillation via Cross-Group Barycenter Alignment
Dataset distillation introduces fairness gaps from subgroup pattern mismatches rather than just imbalance; distilling to a group-agnostic barycenter of predictive information reduces these gaps.