

Publications 


Journal Papers

H. Mayfield, C. Smith, M. Gallagher and M. Hockings. Use of freely available datasets and machine learning methods in predicting deforestation. Environmental Modelling & Software 87:1728, 2017.

P. A. N. Bosman and M. Gallagher. The importance of implementation details and parameter settings in blackbox optimization: a case study on Gaussian estimationofdistribution algorithms and circlesinasquare packing problems. Soft Computing, 2016.

M. Gallagher. "Towards improved benchmarking of blackbox optimization algorithms using clustering problems. Soft Computing, 2016.

R. Morgan and M. Gallagher. Analysing and characterising optimization problems using length scale. Soft Computing, 2015.

W. Luo, M. Gallagher, B. Loveday, S. Ballantyne, J. P. Connor and J. Wiles. Detecting contaminated birthdates using generalized additive models. BMC Bioinformatics 15:185, 2014.

R. Morgan and M. Gallagher. Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements. IEEE Transactions on Evolutionary Computation 18(3): 456461, 2014.

W. Luo, M. Gallagher and J. Wiles. ParameterFree Search of TimeSeries Discord. Journal of Computer Science and Technology 28(2): 300310, 2013.

W. Luo, J. Cao, M. Gallagher and J. Wiles. Estimating the Intensity of Ward Admission and its Effect on Emergency Department Access Block. Statistics in Medicine 32(15): 26812694, 2013.

A. Arief, ZY Dong, M. B. Nappua and M. Gallagher. Under voltage load shedding in power systems with wind turbinedriven doubly fed induction generators. Electric Power Systems Research 96: 91100, 2013.

L. Chen, Y. Liu, M. Gallagher, B. Pailthorpe, S. Sadiq, H. T. Shen and X. Li. Introducing Cloud Computing Topics in Curricula. Journal of Information Systems Education 23(3): 315324, 2012.

R. Morgan and M. Gallagher. Using Landscape Topology to Compare Continuous Metaheuristics: A Framework and Case Study on EDAs and Ridge Structure. Evolutionary Computation 20(2): 277299, 2012.

M. McPartland and M. Gallagher. Reinforcement Learning in First Person Shooter Games. IEEE Transactions on Computational Intelligence and AI in Games 3(1):4356, 2011.

L. You, V. Brusic, M. Gallagher, and M. Boden. Using Gaussian Process with Test Rejection to Detect
TCell Epitopes in Pathogen Genomes. IEEE/ACM Transactions on Computational Biology and Bioinformatics 7(4):741751, 2010.

M. Gallagher and B. Yuan. `A GeneralPurpose Tunable Landscape Generator. IEEE Transactions on
Evolutionary Computation 10(5):590603, 2006.

D. J. Rohde, M. R. Gallagher, M. J. Drinkwater and K. A. Pimbblet. Matching of Catalogues by
Probabilistic Pattern Classification. Monthly Notices of the Royal Astronomical Society 369(1): 214, 2006. arXiv eprint

D. Rohde, M. Drinkwater, M. Gallagher, T. Downs and M. Doyle. Applying Machine Learning to Catalogue Matching in Astrophysics. Monthly Notices of the Royal Astronomical Society 360(1): 6975, June 2005. arXiv eprint

M. Gallagher and M. Frean. PopulationBased Continuous Optimization, Probabilistic Modelling and Mean Shift. Evolutionary Computation 13(1): 2942, 2005.

M. Gallagher and T. Downs. Visualization
of Learning in Multilayer Perceptron Networks using PCA. IEEE
Transactions on Systems, Man and CyberneticsPart B: Cybernetics,
33(1):2834, 2003.

M. Gallagher, T. Downs and I. Wood.
Empirical Evidence for Ultrametric
Structure in Multilayer Perceptron Error Surfaces. Neural Processing Letters, 16(2):177186, 2002.
Conference Papers

S. Saleem and M. Gallagher. Exploratory analysis of clustering problems using a comparison of particle swarm optimization and differential evolution. In Proc. Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), 2017.

X. Hu, M. Gallagher, W. Loveday, J. P. Connor and Janet Wiles. Detecting anomalies in controlled drug prescription data using probabilistic models. In Proc. Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), 2015.

M. Gallagher. Clustering Problems for More Useful Benchmarking of Optimization Algorithms. In Proc. 10th International Conference on Simulated Evolution And Learning (SEAL2014), 2014.

R. Morgan and M. Gallagher. Fitness Landscape Analysis of Circle Packing in a Square Problems. In Proc. 10th International Conference on Simulated Evolution And Learning (SEAL2014), 2014.

K. Mishra and M. Gallagher. A Modified Screening Estimation of Distribution Algorithm for LargeScale Continuous Optimization. To appear, 10th International Conference on Simulated Evolution And Learning (SEAL2014), 2014.

N. Shaker, J. Togelius, G. N. Yannakakis, L. P. K. Satish, V. S.
Ethiraj, S. J. Johansson, R. Reynolds, L. KinnairdHeether, T.
Schumann and M. Gallagher. The Turing Test Track of the 2012 Mario AI Championship: Entries and Evaluation. In Proc. IEEE Symposium on Computational Intelligence and Games (CIG'2013),
pp.291298, 2013.

M. McPartland and M. Gallagher. Game Designers Training First Person Shooter Bots. In Proc. 25th Australasian Joint Conference on Artificial Intelligence (AI'12), to appear, 2012.

R. Morgan and M. Gallagher. Length Scale for Characterising Continuous Optimization Problems. In Parallel Problem Solving from Nature (PPSN XII), pp.407416, Springer, 2012.

M. Gallagher. Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing. In Parallel Problem Solving from Nature (PPSN XII), pp.478487, Springer, 2012. (Note: the experimental results in this paper contain some errors found after publication. Please see the poster presented at PPSN'12 correcting these results.)

M. McPartland and M. Gallagher. Interactively Training First Person Shooter Bots. In Proc. IEEE Symposium on Computational Intelligence and Games (CIG'2012), to appear, 2012.

K. Mishra and M. Gallagher. Variable Screening for Reduced Dependency Modelling in Gaussianbased Continuous Estimation of Distribution Algorithms. In Proc. IEEE World Congress on Computational Intelligence (WCCI'12), 2012.

D. Rohde, M. Gallagher and M. Drinkwater. Astronomical Catalogue Matching as a Mixture Model Problem. In Proc. EBEB 2012  11th Brazilian Bayesian Statistics Meeting, 2012.

W. Luo and M. Gallagher. Faster and ParameterFree Discord Search in QuasiPeriodic Time Series. PacificAsia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), Springer, LNAI 6635, pp.135148, 2011.

R. Morgan and M. Gallagher. When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure. In Parallel Problem Solving from NaturePPSN XI. Springer. pp. 94103, 2010.

W. Luo and M. Gallagher. Unsupervised DRG Upcoding Detection in Healthcare Databases. In Proc. International Workshop on Data Mining Application in Government and Industry 2010 (International Conference on Data Mining Workshops 2010), pp.600605, 2010.

W. Luo, M. Gallagher, D. O'Kane, J. Connor, M. Dooris, C. Roberts, L. Mortimer and J. Wiles.
Visualising
a Statewide Patient Data Collection: A Case Study to Expand the Audience for Healthcare Data.
In Proc. Fourth Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2010).
Conferences in Research and Practice in Information Technology, Volume 108, pp. 4552, 2010.

M. Gallagher. Investigating Circles in a Square Packing Problems as a Realistic Benchmark for
Continuous Metaheuristic Optimization Algorithms. In Proc. MIC 2009: The VIII Metaheuristics
International Conference, 2009.

M. Gallagher. Blackbox optimization benchmarking: results for the BayEDAcG algorithm on the noiseless
function testbed. In Proc. 11th Annual Conference Companion on Genetic and Evolutionary Computation
Conference: Late Breaking Papers (GECCO '09). ACM, pp. 22812286. 2009.

M. Gallagher. Blackbox optimization benchmarking: results for the BayEDAcG algorithm on the noisy
function testbed. In Proc. 11th Annual Conference Companion on Genetic and Evolutionary Computation
Conference: Late Breaking Papers (GECCO '09). ACM, pp. 23832388. 2009.

B. Yuan and M. Gallagher. Convergence analysis of UMDAC with finite populations: a case study on flat
landscapes. In Proc. 11th Annual Conference on Genetic and Evolutionary Computation (GECCO '09).
ACM, pp. 477482. 2009.

N. Wirth and M. Gallagher. An Influence Map Model for Playing Ms. PacMan.
In IEEE Symposium on Computational Intelligence and Games (CIG'08), pp.228233, 2008. (This paper was awarded the Overall Best Paper Award at the Symposium)

M. McPartland and M. Gallagher. Creating a MultiPurpose First Person Shooter Bot with Reinforcement Learning. In IEEE Symposium on Computational Intelligence and Games (CIG'08), pp.143150, 2008.

N. Kumar and M. Gallagher. Gaussian Mixture Models in Estimations of Distribution Algorithms: Implementation Details and Experimental Analysis.
In Proc. 12th AsiaPacific Symposium on Intelligent and Evolutionary Systems (IES'08), pp.5161, 2008.

M. McPartland and M. Gallagher.
Learning to be a Bot: Reinforcement Learning in First Person Shooter Games.
In Proc. Fourth Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE08) , 2008.

F. YH. Yeh and M. Gallagher.
An Empirical Study of the Sample Size Variability of Optimal Active Learning Using
Gaussian Process Regression.
In Proc. IEEE International Joint Conference on Neural Networks (IJCNN), 2008.

M. Gallagher, I. Wood, J. Keith and G. Sofronov.
Bayesian Inference in Estimation of Distribution Algorithms (updated version  September 2008).
Prev. version appears in: Proc. IEEE Congress on Evolutionary
Computation (CEC), pp.127133, 2007.
[Note: The version of this paper published in the CEC'07 proceedings contains some minor typographic errors (specifically in Eqns (5) and (6) and in line 9 of Table III). Please refer to this updated version of the paper for the correct formulae (as actually used in the experiments presented in the paper). Other minor notational modifications have also been made.]

S. Connelly, P. Lindsay and M. Gallagher. An Agent Based Approach to Examining Shared
Situation Awareness. In Proc. IEEE International Conference on Engineering of
Complex Computer Systems (to appear), 2007.

Marcus Gallagher and Mark Ledwich.
Evolving PacMan Players: Can We Learn from Raw Input?
In Proc. IEEE Symposium on
Computational Intelligence and Games, pp.282287, 2007.

Stefan Maetschke, Marcus Gallagher and Mikael Boden.
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins.
In Proc. IEEE Symposium on
Computational Intelligence in Bioinformatics and Computational Biology, pp.367372, 2007.

S. Maetschke, M. Boden and M. Gallagher. Higher order HMMs for Localization Prediction of
Transmembrane Proteins, In Proc. 2006
Workshop on Intelligent Systems for
Bioinformatics (WISB 2006), Hobart, Australia. CRPIT, 73. Boden, M. and
Bailey, T.L., Eds., ACS. 4953.

B. Yuan and M. Gallagher. A Mathematical Modelling Technique for the Analysis of the Dynamics
of a Simple Continuous EDA. Proceedings of 2006 Congress on Evolutionary Computation, pp. 15851591, 2006.

B. Yuan and M. Gallagher. Experimental Results for the Special
Session on RealParameter Optimization at CEC 2005: A Simple, Continuous EDA.
In Proceedings of the 2005 Congress on Evolutionary Computation (CEC'05), pp. 17921799, 2005.

B. Yuan and M. Gallagher. A Hybrid Approach to Parameter
Tuning in Genetic Algorithms. To appear in Proceedings of the 2005 Congress on
Evolutionary Computation (CEC'05), pp. 10961103, 2005.

B. Yuan and M. Gallagher. On the Importance of Diversity Maintenance in Estimation of Distribution Algorithms. In HG. Beyer et al., editors, Proc. Genetic and Evolutionary Computation Conference (GECCO 2005), pp.719726, 2005.

B. Yuan, M. Gallagher and S. Crozier. MRI Magnet Design: Search Space Analysis, EDAs and a RealWorld Problem with Significant Dependences. In HG. Beyer et al., editors, Proc. Genetic and Evolutionary Computation Conference (GECCO 2005), pp.21412148, 2005.

F. YH. Yeh and M. Gallagher. An Empirical Study of Heoffding Racing for Model Selection in kNearest Neighbor Classification. In M. Gallagher et al., editors, Proc. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005), pp. 220227.

B. Yuan and M. Gallagher. Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. In X. Yao et al., editors, Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN'04), pp 172181. Lecture Notes in Computer Science vol.3242, 2004.

D. Rohde, M. Drinkwater, M. Gallagher, T. Downs and M. Doyle. Machine Learning for Matching Astronomy Catalogues. In Z. R. Yang et al., editors, Proc. Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'04). Lecture Notes in Computer Science vol.3177, pp 702707. 2004.

B. Yuan and M. Gallagher. On Building a
Principled Framework for Evaluating and Testing Evolutionary
Algorithms: A Continuous Landscape Generator. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
451458, 2003.

B. Yuan and M. Gallagher. Playing in
Continuous Spaces: Some Analysis and Extension of Populationbased
Incremental Learning. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
443450, 2003.

M. Gallagher and A. Ryan. Learning to
Play PacMan: An Evolutionary, Rulebased Approach. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
24622469, 2003.

W. Y. Leong, J. Homer and M. Gallagher.
Blind Separation of Noisy Mixtures Using the SAND Algorithm. In 7th
International Symposium on DSP and Communication Systems (DSPCS), 2003.

M. Gallagher and P. Deacon.
Neural
Networks and the Classification of Mineralogical Samples Using XRay
Spectra. In L. Wang et. al., editors, Proc. International Conference
on Neural Information Processing (ICONIP'02), pp 26832687, 2002.
IEEE Press, Piscataway, NJ.
 M. Gallagher.
Fitness Distance Correlation of
Neural Network Error Surfaces: A Scalable, Continuous Optimization
Problem. In L. De Raedt and P. Flach (Eds.): European Conference
on Machine Learning (ECML 2001), LNAI2167, pp. 157166, 2001.
 M. Gallagher. An Empirical Investigation of the UserParameters and Performance of Continuous PBIL Algorithms. In B. Widrow et al., editors, Neural Networks for Signal Processing X (Proceedings of the 2000 IEEE Workshop), pp 702710, 2000. IEEE Press, New York.
 M. Gallagher, M. Frean and T.
Downs. RealValued
Evolutionary Optimization using a Flexible Probability Density Estimator.
In W. Banzhaf et al., editors, Proc. Genetic and Evolutionary Computation
Conference (GECCO'99), pp 840846, 1999. Morgan Kaufmann Publishers,
San Francisco, CA.
 M. Gallagher, T. Downs and I. Wood. Ultrametric
Structure in Autoencoder Error Surfaces. In L. Niklasson et al., editors,
Proc.
Eighth International Conference on Artificial Neural Networks (ICANN'98),
pp 177182, 1998. Springer, London.
 M. Gallagher and T. Downs. On
Ultrametricity in Feedforward Neural Network Error Surfaces. In T.
Downs et al., editors, Proc. Ninth Australian Conference on Neural
Networks, pp 236240, 1998. University of Queensland.
 M. Gallagher and T. Downs. Weight
space learning trajectory visualization. In M. Dale et al., editors,
Proc.
Eighth Australian Conference on Neural Networks, pp 5559, 1997.
Telstra Research Laboratories.
 M. Gallagher and T. Downs. Visualization
of learning in neural networks using principal components analysis.
In B. Verma and X. Yao, editors, Proc. International Conference on Computational
Intelligence and Multimedia Applications, pp 327331, 1997. Griffith
University.
Book Chapters
Other

M. Gallagher, J. Hogan and F. Maire (editors). Proceedings of the Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005). Lecture Notes in Computer Science vol.3578, 2005.
 M. Gallagher and M. Frean.
PopulationBased Continuous
Optimization and Probabilistic Modelling. Technical Report
No. MG12001, School of Information Technology and Electrical
Engineering, University of Queensland. 2001.

M. Gallagher.
Multilayer Perceptron Error Surfaces:
Visualization, Structure and Modelling. PhD thesis, Dept. Computer
Science and Electrical Engineering, University of Queensland, 2000.
 T.
Downs, M. Frean and M. Gallagher (editors). Proceedings
of the Ninth Australian Conference on Neural Networks (ACNN'98),
1998. University of Queensland.





