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- W4317541837 abstract "The ability to generalise from a small number of examples is a fundamental challenge in machine learning. To tackle this challenge, we introduce an inductive logic programming (ILP) approach that combines negation and predicate invention. Combining these two features allows an ILP system to generalise better by learning rules with universally quantified body-only variables. We implement our idea in NOPI, which can learn normal logic programs with predicate invention, including Datalog programs with stratified negation. Our experimental results on multiple domains show that our approach can improve predictive accuracies and learning times." @default.
- W4317541837 created "2023-01-20" @default.
- W4317541837 creator A5008794311 @default.
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- W4317541837 date "2023-01-18" @default.
- W4317541837 modified "2023-09-26" @default.
- W4317541837 title "Generalisation Through Negation and Predicate Invention" @default.
- W4317541837 doi "https://doi.org/10.48550/arxiv.2301.07629" @default.
- W4317541837 hasPublicationYear "2023" @default.
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