A Lagrangian duality method approximates best responses for non-linear strategic classification and enables gradient-based training via the Implicit Function Theorem, yielding improved strategic accuracy on standard datasets.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
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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Non-Linear Strategic Classification Made Practical
A Lagrangian duality method approximates best responses for non-linear strategic classification and enables gradient-based training via the Implicit Function Theorem, yielding improved strategic accuracy on standard datasets.
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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.