Michael Bain

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Michael Bain [1] 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.

Selected Publications#

[5] [6]

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 [7]

External Links#

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

References#

1. ↑ Dr Michael Bain | UNSW Research
2. ↑ Michael Bain (1994). Learning Logical Exceptions in Chess. Ph.D. thesis, University of Strathclyde, CitySeerX
3. ↑ Turing Trust - Historical Note by Donald Michie: “In association with the University of Strathclyde, the Turing Institute hosted seven public lectures in the period 1985-93”
4. ↑ Michael Bain (1994). Learning Logical Exceptions in Chess. Ph.D. thesis - Acknowledgements
5. ↑ ICGA Reference Database
6. ↑ dblp: Michael Bain
7. ↑ Operational semantics from Wikipedia

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