Interpolants As Classifiers.pdf

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Preview of Interpolants as Classifiers
🔗 Source: theory.stanford.edu
📊 Size: 353 KB
📄 Pages: 16 pages
⬇️ Downloads: 36

Summary

Interpolants can be viewed as classifiers in supervised machine learning, allowing the use of off-the-shelf classification techniques, such as support vector machines (SVMs), for interpolation. This approach enables the discovery of relevant predicates for program proofs and can handle superficial non-linearities. The technique involves computing samples of values that satisfy given predicates, using an SVM to find lines separating the samples, and obtaining an interpolant from these lines. Experiments demonstrate the feasibility of this approach over various benchmarks from program verification.

Description

Interpolants can be viewed as classifiers in supervised machine learning, allowing the use of off-the-shelf classification techniques, such as support vector...

Technical Information

  • File Format: PDF
  • File Size: 353 KB
  • Pages: 16
  • Language: EN
  • Total Downloads: 36
  • Last Updated: 7 hours ago

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