<div class="csl-bib-body">
<div class="csl-entry">Cipriani, V., & Rossegger, D. (2025). <i>Uniformity in learning structures</i>. arXiv. https://doi.org/10.48550/arXiv.2512.01867</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/223379
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dc.description.abstract
The standard framework for studying learning problems on algebraic structures assumes that the structures in the target family are pairwise nonisomorphic. Under this assumption, the most widely investigated learning criterion--Ex-learning--becomes inherently equivalent to the well-known paradigm of Bc-learning. This paper explores what happens when the nonisomorphism requirement is removed and analyzes the extent to which these two learning criteria remain uniformly equivalent.
en
dc.language.iso
en
-
dc.subject
Algorithmic learning theory
en
dc.subject
Descriptive set theory
en
dc.subject
Computable structure theory
en
dc.subject
uniformity
en
dc.title
Uniformity in learning structures
en
dc.type
Preprint
en
dc.type
Preprint
de
dc.identifier.arxiv
2512.01867
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tuw.researchTopic.id
C4
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E104-02 - Forschungsbereich Computational Logic
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tuw.publisher.doi
10.48550/arXiv.2512.01867
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dc.description.numberOfPages
10
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tuw.author.orcid
0000-0003-3494-9049
-
tuw.publisher.server
arXiv
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
-
wb.sciencebranch.oefos
1010
-
wb.sciencebranch.value
5
-
wb.sciencebranch.value
95
-
item.grantfulltext
none
-
item.languageiso639-1
en
-
item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_816b
-
item.fulltext
no Fulltext
-
item.openairetype
preprint
-
crisitem.author.dept
E104-02 - Forschungsbereich Computational Logic
-
crisitem.author.dept
E104-02 - Forschungsbereich Computational Logic
-
crisitem.author.orcid
0000-0003-3494-9049
-
crisitem.author.parentorg
E104 - Institut für Diskrete Mathematik und Geometrie
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crisitem.author.parentorg
E104 - Institut für Diskrete Mathematik und Geometrie