Composing Neural Learning and Symbolic Reasoning with an Application to Visual Discrimination

1 code implementation • 12 Jul 2019 • Adithya Murali, Atharva Sehgal, Paul Krogmeier, P. Madhusudan

We consider the problem of combining machine learning models to perform higher-level cognitive tasks with clear specifications.

Few-Shot Learning

Horn-ICE Learning for Synthesizing Invariants and Contracts

no code implementations • 26 Dec 2017 • Deepak D'Souza, P. Ezudheen, Pranav Garg, P. Madhusudan, Daniel Neider

We design learning algorithms for synthesizing invariants using Horn implication counterexamples (Horn-ICE), extending the ICE-learning model.

Invariant Synthesis for Incomplete Verification Engines

no code implementations • 15 Dec 2017 • Daniel Neider, Pranav Garg, P. Madhusudan, Shambwaditya Saha, Daejun Park

We propose a framework for synthesizing inductive invariants for incomplete verification engines, which soundly reduce logical problems in undecidable theories to decidable theories.