Andrew Cropper

Andrew Cropper

I am a junior research fellow at Hertford College, University of Oxford. I work on program induction: machine learning computer programs from data. Specifically, I work on inductive logic programming (ILP). I maintain Metagol, an ILP system.

Email CV

Publications

DBLP Google scholar

Journals

Learning efficient logic programs. A. Cropper and S.H. Muggleton. Machine learning (2018). https://doi.org/10.1007/s10994-018-5712-6. slides code

Conferences

SLD-resolution reduction of second-order horn fragments. S. Tourret and A. Cropper. JELIA 2019.
Typed meta-interpretive learning of logic programs. R. Morel, A. Cropper, and L. Ong. JELIA 2019. code
Derivation reduction of metarules in meta-interpretive learning. A. Cropper and S. Tourret. ILP 2018. slides code
Learning higher-order logic programs through abstraction and invention. A. Cropper and S.H. Muggleton. IJCAI 2016. slides code
Learning efficient logical robot strategies involving composable objects. A. Cropper and S.H. Muggleton. IJCAI 2015. slides code
Meta-interpretive learning of data transformation programs. A. Cropper, A. Tamaddoni-Nezhad, and S.H. Muggleton. ILP 2015. slides code
Typed meta-interpretive learning for proof strategies. C. Farquhar, G. Grov, A. Cropper, S.H. Muggleton, and A. Bundy. ILP 2015.
Can predicate invention compensate for incomplete background knowledge? A. Cropper and S.H. Muggleton. SCAI 2015. slides
Logical minimisation of meta-rules within meta-interpretive learning. A. Cropper and S.H. Muggleton. ILP 2014. slides

Workshops

SLD-resolution reduction of second-order Horn fragments. S. Tourret and A. Cropper. Termgraph 2018.
Identifying and inferring objects from textual descriptions of scenes from books. A. Cropper. ICCSW 2014. slides

Extended abstracts

Logic-based inductive synthesis of efficient programs. A. Cropper. IJCAI 2016. slides
Learning efficient logic programs. A. Cropper. IJCAI 2015. slides

Theses

Efficiently learning efficient programs. A. Cropper. PhD thesis, Imperial College London, 2017.
Modelling stock volume using Twitter. A. Cropper. Master's thesis, University of Oxford, 2011.

Talks

Learning efficient logic programs, MIT, USA, September 2018.
Learning efficient logic programs, Dagstuhl workshop in inductive programming, Germany, 2017.
Learning higher-order logic programs, Dagstuhl workshop in inductive programming, Germany, 2017.
Learning efficient logic programs, Machine intelligence 20 workshop on human-like computing, London, UK, 2016.
Logic-based learning of programs from input/output examples, UC Berkeley, USA, July 2016.
Metagol, Dagstuhl workshop in inductive programming, Germany, 2015.
Predicate invention in meta-interpretive learning, Wakayama University, Japan, 2014.