Regular Inference on Artificial Neural Networks - Machine Learning and Knowledge Extraction Access content directly
Conference Papers Year : 2018

Regular Inference on Artificial Neural Networks

Franz Mayr
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  • PersonId : 1043684
Sergio Yovine
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  • PersonId : 1043685

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.
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hal-02060043 , version 1 (07-03-2019)

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Franz Mayr, Sergio Yovine. Regular Inference on Artificial Neural Networks. 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2018, Hamburg, Germany. pp.350-369, ⟨10.1007/978-3-319-99740-7_25⟩. ⟨hal-02060043⟩
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