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Robust Behaviorally Correct Learning

Journal Article journal-article Computer Science ยท Theoretical Computer Science

Abstract

Intuitively, a class of functions is robustly learnable if not only the class itself, but also all of the transformations of the class under natural transformations (such as via general recursive operators) are learnable. Fulk showed the existence of a nontrivial class which is robustly learnable under the criterion Ex. However, several of the hierarchies (such as the anomaly hierarchies for Ex and Bc) do not stand robustly. Fulk left open the question about whether Bc and Ex can be robustly separated. In this paper we resolve this question positively.

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Keywords

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Context

Venue
Information and Computation
Archive span
1987-2026
Indexed papers
3021
Paper id
98029330530708102
v2026.09.13