7 citations · 19 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
Learning programs with magic values
Céline Hocquette, Andrew Cropper
A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice. Learning programs with magic values…
Constraint-driven multi-task learning
Bogdan Cretu, Andrew Cropper
Inductive logic programming is a form of machine learning based on mathematical logic that generates logic programs from given examples and background knowledge. In this project, w…
Learning logic programs by combining programs
Andrew Cropper, Céline Hocquette
The goal of inductive logic programming is to induce a logic program (a set of logical rules) that generalises training examples. Inducing programs with many rules and literals is…
Learning logic programs by discovering where not to search
Andrew Cropper, Céline Hocquette
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises training examples and background knowledge (BK). To improve performance, we introduce a…