Strategic PAC learnability is preserved when hypothesis classes and cost-induced neighborhoods are first-order definable over the reals with exponentiation, controlling sample complexity by formula complexity.
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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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cs.LG 2years
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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Strategic PAC Learnability via Geometric Definability
Strategic PAC learnability is preserved when hypothesis classes and cost-induced neighborhoods are first-order definable over the reals with exponentiation, controlling sample complexity by formula complexity.
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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.