Defines behaviorally realistic strategic classification and proposes Pro-SF framework grounded in prospect theory to model biased agent manipulations in Stackelberg interactions.
Proceedings of the 2018 ACM Conference on Economics and Computation , pages=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A hypothesis class is learnable in this online precision-recall feedback model if and only if it has finite VC dimension, with algorithms achieving regret bounds in realizable and agnostic settings despite ERM failing.
citing papers explorer
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Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
Defines behaviorally realistic strategic classification and proposes Pro-SF framework grounded in prospect theory to model biased agent manipulations in Stackelberg interactions.
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Online Set Learning from Precision and Recall Feedback
A hypothesis class is learnable in this online precision-recall feedback model if and only if it has finite VC dimension, with algorithms achieving regret bounds in realizable and agnostic settings despite ERM failing.