Regular Inference on Artificial Neural Networks View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Franz Mayr , Sergio Yovine

ABSTRACT

This paper explores the general problem of explaining the behavior of artificial neural networks (ANN). The goal is to construct a representation which enhances human understanding of an ANN as a sequence classifier, with the purpose of providing insight on the rationale behind the classification of a sequence as positive or negative, but also to enable performing further analyses, such as automata-theoretic formal verification. In particular, a probabilistic algorithm for constructing a deterministic finite automaton which is approximately correct with respect to an artificial neural network is proposed. More... »

PAGES

350-369

References to SciGraph publications

Book

TITLE

Machine Learning and Knowledge Extraction

ISBN

978-3-319-99739-1
978-3-319-99740-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-99740-7_25

DOI

http://dx.doi.org/10.1007/978-3-319-99740-7_25

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106328946


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157 rdf:type schema:Organization
 




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