14 citations · 23 across the 6 of their papers we have counts for
6 papers
Classifying different criteria for learning algebraic structures
Nikolay Bazhenov, Vittorio Cipriani, Sanjay Jain +2
In the last years there has been a growing interest in the study of learning problems associated with algebraic structures. The framework we use models the scenario in which a lear…
Learning algebraic structures with the help of Borel equivalence relations
Nikolay Bazhenov, Vittorio Cipriani, Luca San Mauro
We study algorithmic learning of algebraic structures. In our framework, a learner receives larger and larger pieces of an arbitrary copy of a computable structure and, at each sta…
Punctual equivalence relations and their (punctual) complexity
Nikolay Bazhenov, Keng Meng Ng, Luca San Mauro +1
The complexity of equivalence relations has received much attention in the recent literature. The main tool for such endeavour is the following reducibility: given equivalence rela…
On the Turing complexity of learning finite families of algebraic structures
Nikolay Bazhenov, Luca San Mauro
In previous work, we have combined computable structure theory and algorithmic learning theory to study which families of algebraic structures are learnable in the limit (up to iso…
Comparing the isomorphism types of equivalence structures and preorders
Nikolay Bazhenov, Luca San Mauro
A general theme of computable structure theory is to investigate when structures have copies of a given complexity . We discuss such problem for the case of equivalence structur…
Learning families of algebraic structures from informant
Nikolay Bazhenov, Ekaterina Fokina, Luca San Mauro
We combine computable structure theory and algorithmic learning theory to study learning of families of algebraic structures. Our main result is a model-theoretic characterization…