Training verified learners with learned verifiers

25 May 2018Krishnamurthy DvijothamSven GowalRobert StanforthRelja ArandjelovicBrendan O'DonoghueJonathan UesatoPushmeet Kohli

This paper proposes a new algorithmic framework, predictor-verifier training, to train neural networks that are verifiable, i.e., networks that provably satisfy some desired input-output properties. The key idea is to simultaneously train two networks: a predictor network that performs the task at hand,e.g., predicting labels given inputs, and a verifier network that computes a bound on how well the predictor satisfies the properties being verified... (read more)

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