7 citations · 19 across the 17 of their papers we have counts for
25 papers
Learning logic programs by finding minimal unsatisfiable subprograms
Andrew Cropper, Céline Hocquette
The goal of inductive logic programming (ILP) is to search for a logic program that generalises training examples and background knowledge. We introduce an ILP approach that identi…
Learning big logical rules by joining small rules
Céline Hocquette, Andreas Niskanen, Rolf Morel +2
A major challenge in inductive logic programming is learning big rules. To address this challenge, we introduce an approach where we join small rules to learn big rules. We impleme…
Learning MDL logic programs from noisy data
Céline Hocquette, Andreas Niskanen, Matti Järvisalo +1
Many inductive logic programming approaches struggle to learn programs from noisy data. To overcome this limitation, we introduce an approach that learns minimal description length…
Learning logic programs by discovering higher-order abstractions
Céline Hocquette, Sebastijan Dumančić, Andrew Cropper
We introduce the higher-order refactoring problem, where the goal is to compress a logic program by discovering higher-order abstractions, such as map, filter, and fold. We impleme…
Generalisation Through Negation and Predicate Invention
David M. Cerna, Andrew Cropper
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…
Relational program synthesis with numerical reasoning
Céline Hocquette, Andrew Cropper
Program synthesis approaches struggle to learn programs with numerical values. An especially difficult problem is learning continuous values over multiple examples, such as interva…