• DOI:10.1609/AAAI.V33I01.33012662
Corpus ID: 54051467

Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees

@inproceedings{Bagnall2019CertifyingTT,
  title={Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees},
  author={Alexander Bagnall and G. Stewart},
  booktitle={AAAI},
  year={2019}
}

Alexander Bagnall, G. Stewart

Published in AAAI 2019

Computer Science

We present MLCERT, a novel system for doing practical mechanized proof of the generalization of learning procedures, bounding expected error in terms of training or test error. MLCERT is mechanized in that we prove generalization bounds inside the theorem prover Coq; thus the bounds are machine checked by Coq’s proof checker. MLCERT is practical in that we extract learning procedures defined in Coq to executable code; thus procedures with proved generalization bounds can be trained and deployed… CONTINUE READING

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