Formalizes improvement-aware strategic classification for linear classifiers under single-index models, proves the strategic-optimal classifier is a parallel shift of the Bayes boundary, and supplies PAC guarantees with a plug-in algorithm evaluated on datasets.
arXiv preprint arXiv:2505.05594 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.LG 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
Introduces IFSC framework modeling peer imitation in individual fairness-aware strategic classification to improve fairness consistency under interdependent manipulations.
Introduces partial fairness awareness (PFA) and a belief-guided mechanism allowing strategic agents to align beliefs with a hidden grounding fairness constraint via iterative interaction.
citing papers explorer
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Linear Strategic Classification with Endogenous Improvements
Formalizes improvement-aware strategic classification for linear classifiers under single-index models, proves the strategic-optimal classifier is a parallel shift of the Bayes boundary, and supplies PAC guarantees with a plug-in algorithm evaluated on datasets.
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Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation
Introduces IFSC framework modeling peer imitation in individual fairness-aware strategic classification to improve fairness consistency under interdependent manipulations.
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Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents
Introduces partial fairness awareness (PFA) and a belief-guided mechanism allowing strategic agents to align beliefs with a hidden grounding fairness constraint via iterative interaction.