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Edit Distance Kernelization of NP Theorem Proving For Polynomial-Time Machine Learning of Proof Heuristics

  • David WindridgeEmail author
  • Florian Kammüller
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 70)

Abstract

We outline a general strategy for the application of edit-distance based kernels to NP Theorem Proving in order to allow for polynomial-time machine learning of proof heuristics without the loss of sequential structural information associated with conventional feature-based machine learning. We provide a general short introduction to logic and proof considering a few important complexity results to set the scene and highlight the relevance of our findings.

Keywords

Machine learning Theorem proving Kernel methods 

Notes

Acknowledgements

The first author would like to acknowledge financial support from the Horizon 2020 European Research project DREAMS4CARS (number 731593).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Middlesex University LondonLondonUK

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