Michael Bain

Home * People * Michael Bain

Michael Bain

Michael (Mike) Bain,
a computer scientist and senior lecturer at School of Computer Science & Engineering, University of New South Wales in Sydney, New South Wales, Australia. His research interests include machine learning, inductive logic programming, behavioural cloning, concept analysis and bioinformatics.

Learning KRK

In 1994, Michael Bain defended his Ph.D. thesis in machine learning at University of Strathclyde, Glasgow, Scotland, titled Learning Logical Exceptions in Chess which covers the endgame KRK . Donald Michie had employed him at the Turing Institute, until 1993 associated with Strathclyde , to work on the US Army chess project, and where he researched on machine learning along with Jean Hayes Michie, Stephen Muggleton and Ivan Bratko .

Selected Publications

1989

• Donald Michie, Michael Bain (1989). Machines That Learn and Machines That Teach. SCAI 1989
• Stephen Muggleton, Michael Bain, Jean Hayes Michie, Donald Michie (1989). An Experimental Comparison of Human and Machine Learning Formalisms. 6. ML 1989, pdf

1990

• Ashwin Srinivasan, Stephen Muggleton, Michael Bain (1992). Distinguishing exceptions from noise in non-monotonic Learning. ILP92, pdf
• Michael Bain (1994). Learning Logical Exceptions in Chess. Ph.D. thesis, University of Strathclyde, CitySeerX
• Michael Bain, Stephen Muggleton (1994). Learning Optimal Chess Strategies. Machine Intelligence 13
• Michael Bain, Ashwin Srinivasan (1995). Inductive logic programming with large-scale unstructured data. Machine Intelligence 14
• Stephen Muggleton, Michael Bain (1999). Analogical Prediction. ILP 1999, pdf

2000 ...

• Michael Bain, Stephen Muggleton, Ashwin Srinivasan (2000). Generalising Closed World Specialisation: A Chess End Game Application. CitySeerX
• Michael Bain (2002). Structured Features from Concept Lattices for Unsupervised Learning and Classification. Australian Joint Conference on Artificial Intelligence 2002
• Michael Bain (2004). Predicate Invention and the Revision of First-Order Concept Lattices. ICFCA 2004

2010 ...

• Michael Bain (2010). Structured Induction. Encyclopedia of Machine Learning 2010
• Ashwin Srinivasan, Michael Bain (2011). Knowledge-Guided Identification of Petri Net Models of Large Biological Systems. ILP 2011
• Xinqi Zhu, Michael Bain (2017). B-CNN: Branch Convolutional Neural Network for Hierarchical Classification. arXiv:1709.09890, GitHub - zhuxinqimac/B-CNN: Sample code of B-CNN paper
• Ashwin Srinivasan, Lovekesh Vig, Michael Bain (2018). Logical Explanations for Deep Relational Machines Using Relevance Information. arXiv:1807.00595
• Michael Bain, Ashwin Srinivasan (2018). Identification of biological transition systems using meta-interpreted logic programs. Machine Learning, Vol. 107, No. 7

External Links

• Dr Michael Bain | UNSW Research
• UCI Machine Learning Repository: Chess (King-Rook vs. King) Data Set

References

Up one level