Partial learning of recursively enumerable languages
TLDR
This paper constitutes a substantial extension to prior work on partial learning and studies several typical learning criteria in the model of partial learning of r.e. sets in the recursion-theoretic framework of inductive inference, leading to interesting consequences about the structural properties of the collection of classes learnable under these criteria.About:
This article is published in Theoretical Computer Science.The article was published on 2016-03-21 and is currently open access. It has received 3 citations till now. The article focuses on the topics: Algorithmic learning theory & Stability (learning theory).read more
Citations
More filters
Proceedings Article
On the Help of Bounded Shot Verifiers, Comparators and Standardisers for Learnability in Inductive Inference
TL;DR: The main goal of this paper is to figure out to what extent verifiability, comparability, and standardisability are helpful for the inductive inference of classes of recursively enumerable languages.
Book ChapterDOI
Combining Models of Approximation with Partial Learning
TL;DR: This work solves an open problem of Fulk and Jain by showing that there is a learner which approximates and partially identifies every recursive function by outputting a sequence of hypotheses which, in addition, are also almost all finite variants of the target function.
Posted Content
Combining Models of Approximation with Partial Learning
TL;DR: In this paper, it was shown that there is a learner which approximates and partially identifies every recursive function by outputting a sequence of hypotheses which are also almost all finite variants of the target function.
References
More filters
Journal ArticleDOI
Theory of Recursive Functions and Effective Computability.
Solomon Feferman,Hartley Rogers +1 more
TL;DR: Central concerns of the book are related theories of recursively enumerable sets, of degree of un-solvability and turing degrees in particular and generalizations of recursion theory.
Journal ArticleDOI
Language identification in the limit
TL;DR: It was found that theclass of context-sensitive languages is learnable from an informant, but that not even the class of regular languages is learningable from a text.
Book
Theory of Recursive Functions and Effective Computability
TL;DR: In this paper, the authors discuss related theories of recursively enumerable sets, degree of un-solvability and turing degrees in particular, and generalizations of recursion theory.
Journal ArticleDOI
Inductive inference of formal languages from positive data
TL;DR: A theorem characterizing when an indexed family of nonempty recursive formal languages is inferrable from positive data is proved, and other useful conditions for inference frompositive data are obtained.
Book
Systems That Learn: An Introduction to Learning Theory
TL;DR: Systems That Learn presents a mathematical framework for the study of learning in a variety of domains that provides the basic concepts and techniques of learning theory as well as a comprehensive account of what is currently known about a range of learning paradigms.
Related Papers (5)
Partially distribution-free learning of regular languages from positive samples
Alexander Clark,Franck Thollard +1 more
Set-driven and rearrangement-independent learning of recursive languages
Steffen Lange,Thomas Zeugmann +1 more