5 citations · 5 across the 6 of their papers we have counts for
6 papers
The tolerant learning hierarchy for c.e. sets
Vittorio Cipriani, Martin Ritter, Luca San Mauro
Learning from positive data models a scenario in which a learner receives longer and longer initial segments of an enumeration of an unknown set and repeatedly outputs a conjecture…
On statistical learning of graphs
Vittorio Cipriani, Valentino Delle Rose, Luca San Mauro +1
We study PAC and online learnability of hypothesis classes formed by copies of a countably infinite graph G, where each copy is induced by permuting G's vertices. This corresponds…
On the learning power of Friedman-Stanley jumps
Vittorio Cipriani, Alberto Marcone, Luca San Mauro
Recently, a surprising connection between algorithmic learning of algebraic structures and descriptive set theory has emerged. Following this line of research, we define the learni…
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…
The Weihrauch lattice at the level of : the Cantor-Bendixson theorem
Vittorio Cipriani, Alberto Marcone, Manlio Valenti
This paper continues the program connecting reverse mathematics and computable analysis via the framework of Weihrauch reducibility. In particular, we consider problems related to…
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…