Andrew Cropper

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

I am looking for students/collaborators to work on program induction, so please contact me if interested.

Email CV

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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

• 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.

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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.