Marcus Gallagher is an Associate Professor in the Artificial Intelligence Group in the School of Information Technology and Electrical Engineering. His research interests are in artificial intelligence, including optimisation and machine learning. He is particularly interested in understanding the relationship between algorithm performance and problem structure via benchmarking. My work includes cross-disciplinary collaborations and real-world applications of AI techniques.
Dr Gallagher received his BCompSc and GradDipSc from the University of New England, Australia in 1994 and 1995 respectively, and his PhD in 2000 from the University of Queensland, Australia. He also completed a GradCert (Higher Education) in 2010.
Conference Publication: Modularity Based Linkage Model For Neuroevolution
Qiao, Yukai and Gallagher, Marcus (2023). Modularity Based Linkage Model For Neuroevolution. New York, NY, USA: ACM. doi: 10.1145/3583133.3590648
Conference Publication: Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning
Munn, Humphrey and Gallagher, Marcus (2023). Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. International Joint Conference on Neural Networks (IJCNN), Broadbeach Australia, Jun 18-23, 2023. NEW YORK: IEEE. doi: 10.1109/ijcnn54540.2023.10191234
Journal Article: Guest editorial: special issue on evolutionary computation for games
Schrum, Jacob, Liu, Jialin, Browne, Cameron, Ekárt, Anikó and Gallagher, Marcus (2023). Guest editorial: special issue on evolutionary computation for games. IEEE Transactions on Games, 15 (1), 1-4. doi: 10.1109/tg.2022.3225730
(2021–2022) University of Melbourne
Machine Learning for Automated Network Anomaly Detection, Cyber Security and Analysis - Phase II
(2019) Innovation Connections
Machine Learning for Automated Network Anomaly detection and Analysis
(2018–2019) Innovation Connections
Parsimony and Performance in Rule-Based Evolutionary Reinforcement Learning
(2023) Doctor Philosophy
Improving neuroevolution using ideas from deep learning and optimization
Doctor Philosophy
Fitness Landscape Features as Curriculum Ordering Measures for Reinforcement Learning
Doctor Philosophy
AI 2020: advances in artificial intelligence
Marcus Gallagher, Nour Moustafa and Erandi Lakshika eds. (2020). AI 2020: advances in artificial intelligence. Lecture Notes in Computer Science, Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-64984-5
Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks
Yuan, B. and Gallagher, M. (2007). Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks. Parameter Setting in Evolutionary Algorithms. (pp. 121-142) edited by Lobo, F. G., Lima, C. F. and Michalewicz, Z.. Berlin, Heidelberg, Germany: Springer-Verlag. doi: 10.1007/978-3-540-69432-8_6
Guest editorial: special issue on evolutionary computation for games
Schrum, Jacob, Liu, Jialin, Browne, Cameron, Ekárt, Anikó and Gallagher, Marcus (2023). Guest editorial: special issue on evolutionary computation for games. IEEE Transactions on Games, 15 (1), 1-4. doi: 10.1109/tg.2022.3225730
From zero-shot machine learning to zero-day attack detection
Sarhan, Mohanad, Layeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2023). From zero-shot machine learning to zero-day attack detection. International Journal of Information Security, 22 (4), 947-959. doi: 10.1007/s10207-023-00676-0
Opioid dispensing 2008–18: a Queensland perspective
Suckling, Benita, Pattullo, Champika, Donovan, Peter, Gallagher, Marcus, Patanwala, Asad and Penm, Jonathan (2023). Opioid dispensing 2008–18: a Queensland perspective. Australian Health Review, 47 (2), 217-225. doi: 10.1071/ah22247
Feature extraction for machine learning-based intrusion detection in IoT networks
Sarhan, Mohanad, Layeghy, Siamak, Moustafa, Nour, Gallagher, Marcus and Portmann, Marius (2022). Feature extraction for machine learning-based intrusion detection in IoT networks. Digital Communications and Networks. doi: 10.1016/j.dcan.2022.08.012
Caldwell, Sabrina, Sweetser, Penny, O'donnell, Nicholas, Knight, Matthew J., Aitchison, Matthew, Gedeon, Tom, Johnson, Daniel, Brereton, Margot, Gallagher, Marcus and Conroy, David (2022). An agile new research framework for hybrid human-AI teaming: trust, transparency, and transferability. ACM Transactions on Interactive Intelligent Systems, 12 (3) 17, 1-36. doi: 10.1145/3514257
Using regression models for characterizing and comparing black box optimization problems
Saleem, Sobia and Gallagher, Marcus (2021). Using regression models for characterizing and comparing black box optimization problems. Swarm and Evolutionary Computation, 68 100981, 1-10. doi: 10.1016/j.swevo.2021.100981
Considerations for selecting a machine learning technique for predicting deforestation
Mayfield, Helen J. , Smith, Carl , Gallagher, Marcus and Hockings, Marc (2020). Considerations for selecting a machine learning technique for predicting deforestation. Environmental Modelling and Software, 131 104741, 1-10. doi: 10.1016/j.envsoft.2020.104741
Symons, Martyn, Feeney, Gerald F. X., Gallagher, Marcus R., Young, Ross Mc D. and Connor, Jason P. (2020). Predicting alcohol dependence treatment outcomes: A prospective comparative study of clinical psychologists vs ‘trained’ machine learning models. Addiction, 115 (11) add.15038, 2164-2175. doi: 10.1111/add.15038
Network analysis and visualisation of opioid prescribing data
Hu, Xuelei, Gallagher, Marcus, Loveday, William, Dev, Abhilash and Connor, Jason P. (2019). Network analysis and visualisation of opioid prescribing data. IEEE Journal of Biomedical and Health Informatics, 24 (5) 8822723, 1-9. doi: 10.1109/jbhi.2019.2939028
Symons, Martyn, Feeney, Gerald F.X., Gallagher, Marcus R., Young, Ross McD. and Connor, Jason P. (2019). Machine learning vs addiction therapists: a pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication. Journal of Substance Abuse Treatment, 99, 156-162. doi: 10.1016/j.jsat.2019.01.020
Quantitative measure of nonconvexity for black-box continuous functions
Tamura, Kenichi and Gallagher, Marcus (2019). Quantitative measure of nonconvexity for black-box continuous functions. Information Sciences, 476, 64-82. doi: 10.1016/j.ins.2018.10.009
Direct feature evaluation in black-box optimization using problem transformations
Saleem, Sobia, Gallagher, Marcus and Wood, Ian (2018). Direct feature evaluation in black-box optimization using problem transformations. Evolutionary Computation, 27 (1), 75-98. doi: 10.1162/evco_a_00247
Pedroso, Dorival M., Bonyadi, Mohammad Reza and Gallagher, Marcus (2017). Parallel evolutionary algorithm for single and multi-objective optimisation: Differential evolution and constraints handling. Applied Soft Computing, 61, 995-1012. doi: 10.1016/j.asoc.2017.09.006
Multiple community energy storage planning in distribution networks using a cost-benefit analysis
Sardi, Junainah, Mithulananthan, N., Gallagher, M. and Hung, Duong Quoc (2017). Multiple community energy storage planning in distribution networks using a cost-benefit analysis. Applied Energy, 190, 453-463. doi: 10.1016/j.apenergy.2016.12.144
Use of freely available datasets and machine learning methods in predicting deforestation
Mayfield, Helen, Smith, Carl, Gallagher, Marcus and Hockings, Marc (2017). Use of freely available datasets and machine learning methods in predicting deforestation. Environmental Modelling and Software, 87, 17-28. doi: 10.1016/j.envsoft.2016.10.006
Bosman, Peter A. N. and Gallagher, Marcus (2016). The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems. Soft Computing, 22 (4), 1-15. doi: 10.1007/s00500-016-2408-3
Towards improved benchmarking of black-box optimization algorithms using clustering problems
Gallagher, Marcus (2016). Towards improved benchmarking of black-box optimization algorithms using clustering problems. Soft Computing, 20 (10), 1-15. doi: 10.1007/s00500-016-2094-1
Analysing and characterising optimization problems using length scale
Morgan, Rachel and Gallagher, Marcus (2015). Analysing and characterising optimization problems using length scale. Soft Computing, 21 (7), 1735-1752. doi: 10.1007/s00500-015-1878-z
Detecting contaminated birthdates using generalized additive models
Luo, Wei, Gallagher, Marcus, Loveday Bill, Ballantyne, Susan, Connor, Jason P. and Wiles, Janet (2014). Detecting contaminated birthdates using generalized additive models. BMC Bioinformatics, 15 (1) 185. doi: 10.1186/1471-2105-15-185
Morgan, Rachael and Gallagher, Marcus (2014). Sampling techniques and distance metrics in high dimensional continuous landscape analysis: limitations and improvements. IEEE Transactions On Evolutionary Computation, 18 (3) 6595542, 456-461. doi: 10.1109/TEVC.2013.2281521
Estimating the intensity of ward admission and its effect on emergency department access block
Luo, Wei, Cao, Jiguo, Gallagher, Marcus R. and Wiles, Janet H. (2013). Estimating the intensity of ward admission and its effect on emergency department access block. Statistics In Medicine, 32 (15), 2681-2694. doi: 10.1002/sim.5684
Parameter-free search of time-series discord
Luo, Wei, Gallagher, Marcus and Wiles, Janet (2013). Parameter-free search of time-series discord. Journal of Computer Science and Technology, 28 (2), 300-310. doi: 10.1007/s11390-013-1330-8
Arief, Ardiaty, Dong, ZhaoYang, Nappu, Muhammad Bachtiar and Gallagher, Marcus (2013). Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators. Electric Power Systems Research, 96, 91-100. doi: 10.1016/j.epsr.2012.10.013
Morgan, R. and Gallagher, M. (2012). Using landscape topology to compare continuous metaheuristics: a framework and case study on EDAs and ridge structure. Evolutionary Computation, 20 (2), 277-299. doi: 10.1162/EVCO_a_00070
Introducing cloud computing topics in curricula
Chen, Ling, Liu, Yang, Gallagher, Marcus, Pailthorpe, Bernard, Sadiq, Shazia, Shen, Heng Tao and Li, Xue (2012). Introducing cloud computing topics in curricula. Journal of Information Systems Education, 23 (3), 315-324.
Reinforcement learning in first person shooter games
McPartland, Michelle and Gallagher, Marcus (2011). Reinforcement learning in first person shooter games. Ieee Transactions On Computational Intelligence and Ai in Games, 3 (1) 5672586, 43-56. doi: 10.1109/TCIAIG.2010.2100395
Using Gaussian process with test rejection to detect T-Cell epitopes in pathogen genomes
You, Liwen, Brusic, Vladimir, Gallagher, Marcus and Boden, Mikael (2010). Using Gaussian process with test rejection to detect T-Cell epitopes in pathogen genomes. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 7 (4) 4695825, 741-751. doi: 10.1109/TCBB.2008.131
Combining meta-EAs and racing for difficult EA parameter tuning tasks
Yuan, Bo and Gallagher, Marcus (2007). Combining meta-EAs and racing for difficult EA parameter tuning tasks. Studies in Computational Intelligence, 54, 121-142. doi: 10.1007/978-3-540-69432-8_6
Parameter interdependence and uncertainty induced by lumping in a hydrologic model
Gallagher, MR and Doherty, J (2007). Parameter interdependence and uncertainty induced by lumping in a hydrologic model. Water Resources Research, 43 (5) W05421. doi: 10.1029/2006WR005347
Yin, Hujun, Gallagher, Marcus and Magdon-Ismail, Malik (2006). Introduction. International Journal of Neural Systems, 16 (5), v-vi.
A general-purpose tunable landscape generator
Gallagher, Marcus and Yuan, Bo (2006). A general-purpose tunable landscape generator. IEEE Transactions On Evolutionary Computation, 10 (5), 590-603. doi: 10.1109/TEVC.2005.863628
Matching of catalogues by probabilistic pattern classification
Rohde, D. J., Gallagher, M. R., Drinkwater, M. J. and Pimbblet, K. A. (2006). Matching of catalogues by probabilistic pattern classification. Monthly Notices of The Royal Astronomical Society, 369 (1), 2-14. doi: 10.1111/j.1365-2966.2006.10304.x
Lecture Notes in Computer Science: Preface
Gallagher, Marcus, Hogan, James and Maire, Frederic (2005). Lecture Notes in Computer Science: Preface. Lecture Notes in Computer Science, 3578
Applying machine learning to catalogue matching in astrophysics
Rohde, D. J., Drinkwater, M. J., Gallagher, M. R., Downs, T. and Doyle, M. T. (2005). Applying machine learning to catalogue matching in astrophysics. Monthly Notices of The Royal Astronomical Society, 360 (1), 69-75. doi: 10.1111/j.1365-2966.2005.08930.x
Population-based continuous optimization, probabilistic modelling and mean shift
Gallagher, M. and Frean, M. (2005). Population-based continuous optimization, probabilistic modelling and mean shift. Evolutionary Computation, 13 (1), 29-42. doi: 10.1162/1063656053583478
Machine learning for matching astronomy catalogues
Rohde, David, Drinkwater, Michael, Gallagher, Marcus, Downs, Tom and Doyle, Marianne (2004). Machine learning for matching astronomy catalogues. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3177, 702-707.
Statistical racing techniques for improved empirical evaluation of evolutionary algorithms
Yuan, Bo and Gallagher, Marcus (2004). Statistical racing techniques for improved empirical evaluation of evolutionary algorithms. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3242, 172-181.
Visualization of learning in multilayer perceptron networks using principal component analysis
Gallagher, M. R. and Downs, T. (2003). Visualization of learning in multilayer perceptron networks using principal component analysis. IEEE transactions on systems, man and cybernetics. Part B, Cybernetics Part B-cybernetics, 33 (1), 28-34. doi: 10.1109/TSMCB.2003.808183
Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces
Gallagher, Marcus, Downs, Tom and Wood, Ian (2002). Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces. Neural Processing Letters, 16 (2), 177-186. doi: 10.1023/A:1019956303894
Empirical investigation of the user-parameters and performance of continuous PBIL algorithms
Gallagher, Marcus (2000). Empirical investigation of the user-parameters and performance of continuous PBIL algorithms. Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, 2, 702-710.
UMTS: The next generation of mobile radio
Gallagher, Mark and Webb, William (1999). UMTS: The next generation of mobile radio. IEE Review, 45 (2), 59-63.
A flexible, low-cost, ionospheric sounding system
Bartlett, A., Darnell, M. and Gallagher, M. (1996). A flexible, low-cost, ionospheric sounding system. IEE Colloquium (Digest) (24)
An embedded HF frequency management system
Ripley, M. W., Darnell, M. and Gallagher, M. (1996). An embedded HF frequency management system. IEE Colloquium (Digest) (24)
Passive monitoring for improved HF frequency management
Piggin, P. W., Darnell, M. and Gallagher, M. (1996). Passive monitoring for improved HF frequency management. IEE Colloquium (Digest) (24)
The XK8 engine management system and electronic engine control module
Gallagher, Mark (1996). The XK8 engine management system and electronic engine control module. IEE Colloquium (Digest) (281)
Redundancy and its implications in TLM diffusion models
Pulko, S. H., Wilkinson, A. J. and Gallagher, M. (1993). Redundancy and its implications in TLM diffusion models. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 6 (2), 135-144. doi: 10.1002/jnm.1660060206
Modularity Based Linkage Model For Neuroevolution
Qiao, Yukai and Gallagher, Marcus (2023). Modularity Based Linkage Model For Neuroevolution. New York, NY, USA: ACM. doi: 10.1145/3583133.3590648
Munn, Humphrey and Gallagher, Marcus (2023). Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. International Joint Conference on Neural Networks (IJCNN), Broadbeach Australia, Jun 18-23, 2023. NEW YORK: IEEE. doi: 10.1109/ijcnn54540.2023.10191234
Examining average and discounted reward optimality criteria in reinforcement learning
Dewanto, Vektor and Gallagher, Marcus (2022). Examining average and discounted reward optimality criteria in reinforcement learning. 35th Australasian Joint Conference on Artificial Intelligence (AI), Perth, Australia, 5-9 December 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-22695-3_56
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS
Bishop, Jordan T., Gallagher, Marcus and Browne, Will N. (2022). Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. Genetic and Evolutionary Computation Conference (GECCO), Boston, MA, United States, 9-13 July 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3512290.3528767
Graph neural network-based android malware classification with jumping knowledge
Lo, Wai Weng, Layeghy, Siamak, Sarhan, Mohanad, Gallagher, Marcus and Portmann, Marius (2022). Graph neural network-based android malware classification with jumping knowledge. 2022 IEEE Conference on Dependable and Secure Computing (DSC), Edinburgh, United Kingdom, 22-24 June 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/dsc54232.2022.9888878
E-GraphSAGE: a graph neural network based intrusion detection system for IoT
Lo, Wai Weng, Layeghy, Siamak, Sarhan, Mohanad, Gallagher, Marcus and Portmann, Marius (2022). E-GraphSAGE: a graph neural network based intrusion detection system for IoT. NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary, 25-29 April 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/noms54207.2022.9789878
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies
Bishop, Jordan T., Gallagher, Marcus and Browne, Will N. (2021). A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. GECCO '21: Genetic and Evolutionary Computation Conference, Lille, France, 10 - 14 July, 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3449726.3463198
Avoiding kernel fixed points: Computing with ELU and GELU infinite networks
Tsuchida, Russell, Pearce, Tim, van der Heide, Chris, Roosta, Fred and Gallagher, Marcus (2021). Avoiding kernel fixed points: Computing with ELU and GELU infinite networks. 35th AAAI Conference on Artificial Intelligence, AAAI 2021, Online, 2 - 9 February 2021. Menlo Park, CA United States: Association for the Advancement of Artificial Intelligence.
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks
Tsuchida, Russell, Pearce, Tim, van der Heide, Chris, Roosta, Fred and Gallagher, Marcus (2021). Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence, Electr Network, Feb 02-09, 2021. PALO ALTO: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Optimality-based analysis of xcsf compaction in discrete reinforcement learning
Bishop, Jordan T. and Gallagher, Marcus (2020). Optimality-based analysis of xcsf compaction in discrete reinforcement learning. 16th International Conference on Parallel Problem Solving from Nature PPSN 2020, Leiden, Netherlands, September 5-9, 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-58115-2_33
A novel mutation operator for variable length algorithms
Van Ryt, Saskia, Gallagher, Marcus and Wood, Ian (2020). A novel mutation operator for variable length algorithms. AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint Conference, Canberra, ACT, Australia, 29 - 30 November 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-64984-5_14
Qiao, Yukai and Gallagher, Marcus (2020). An Implementation and Experimental Evaluation of a Modularity Explicit Encoding Method for Neuroevolution on Complex Learning Tasks. 33rd Australasian Joint Conference, AI 2020, Canberra, ACT Australia, 29–30 November 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-64984-5_11
Fitness landscape features and reward shaping in reinforcement learning policy spaces
du Preez-Wilkinson, Nathaniel and Gallagher, Marcus (2020). Fitness landscape features and reward shaping in reinforcement learning policy spaces. Parallel Problem Solving from Nature – PPSN XVI, Leiden, The Netherlands, 5 - 9 September 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-58115-2_35
Reversible jump probabilistic programming
Roberts, David A., Gallagher, Marcus and Taimre, Thomas (2019). Reversible jump probabilistic programming. The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), Naha, Okinawa, Japan, 16 - 18 April 2019. Brookline, MA, United States: ML Research Press.
Exchangeability and kernel invariance in trained MLPs
Tsuchida, Russell, Roosta, Fred and Gallagher, Marcus (2019). Exchangeability and kernel invariance in trained MLPs. Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19, Macao, China, 10-16 August 2019. Marina del Rey, CA USA: International Joint Conferences on Artificial Intelligence. doi: 10.24963/ijcai.2019/498
Exploring the MLDA benchmark on the Nevergrad platform
Rapin, Jeremy, Gallagher, Marcus, Kerschke, Pascal, Preuss, Mike and Teytaud, Olivier (2019). Exploring the MLDA benchmark on the Nevergrad platform. 2019 Genetic and Evolutionary Computation Conference, GECCO 2019, Prague, Czech Republic, 13 - 17 July 2019. New York, New York, USA: Association for Computing Machinery, Inc. doi: 10.1145/3319619.3326830
Fitness landscape analysis in data-driven optimization: An investigation of clustering problems
Gallagher, Marcus (2019). Fitness landscape analysis in data-driven optimization: An investigation of clustering problems. IEEE Congress on Evolutionary Computation (IEEE CEC), Wellington, New Zealand, 10-13 June, 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/CEC.2019.8790323
A model-based framework for black-box problem comparison using gaussian processes
Saleem, Sobia, Gallagher, Marcus and Wood, Ian (2018). A model-based framework for black-box problem comparison using gaussian processes. 15th International Conference on Parallel Problem Solving from Nature, PPSN 2018, Coimbra, Portugal, 8-12 September 2018. Cham, Switzerland: Springer Verlag. doi: 10.1007/978-3-319-99259-4_23
du Preez-Wilkinson, Nathaniel, Gallagher, Marcus and Hu, Xuelei (2018). Flood-fill Q-learning updates for learning redundant policies in order to interact with a computer screen by clicking. 31st Australasian Joint Conference on Artificial Intelligence, AI 2018, Wellington,, December 11, 2018-December 14, 2018. Germany: Springer Verlag. doi: 10.1007/978-3-030-03991-2_49
Intra-task curriculum learning for faster reinforcement learning in video games
du Preez-Wilkinson, Nathaniel, Gallagher, Marcus and Hu, Xuelei (2018). Intra-task curriculum learning for faster reinforcement learning in video games. 31st Australasian Joint Conference on Artificial Intelligence (AI 2018), Wellington, New Zealand, 11-14 December 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-03991-2_6
Invariance of weight distributions in rectified MLPs
Tsuchida, Russell, Roosta-Khorasani, Farbod and Gallagher, Marcus (2018). Invariance of weight distributions in rectified MLPs. 35th International Conference on Machine Learning, Stockholm, Sweden, 10-15 July 2018. Cambridge, MA, United States: M I T Press.
Saleem, Sobia and Gallagher, Marcus (2017). Exploratory analysis of clustering problems using a comparison of particle swarm optimization and differential evolution. 3rd Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, Geelong, VIC, Australia, 31 January – 2 February 2017. Heidelberg, Germany: Springer . doi: 10.1007/978-3-319-51691-2_27
Detecting anomalies in controlled drug prescription data using probabilistic models
Hu, Xuelei, Gallagher, Marcus, Loveday, William, Connor, Jason P. and Wiles, Janet (2015). Detecting anomalies in controlled drug prescription data using probabilistic models. 1st Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015, Newcastle, NSW Australia, 5 - 7 February 2015. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-14803-8_26
A modified screening estimation of distribution algorithm for large-scale continuous optimization
Mishra, Krishna Manjari and Gallagher, Marcus (2014). A modified screening estimation of distribution algorithm for large-scale continuous optimization. 10th International Conference SEAL 2014, Dunedin, New Zealand, 15-18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_11
Clustering problems for more useful benchmarking of optimization algorithms
Gallagher, Marcus (2014). Clustering problems for more useful benchmarking of optimization algorithms. 10th International Conference SEAL 2014, Dunedin, New Zealand, 15-18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_12
Fitness landscape analysis of circles in a square packing problems
Morgan, Rachael and Gallagher, Marcus (2014). Fitness landscape analysis of circles in a square packing problems. 10th International Conference, SEAL 2014, Dunedin, New Zealand, 15 - 18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_39
The Turing test track of the 2012 Mario AI championship: entries and evaluation
Shaker, Noor, Togelius, Julian, Yannakakis, Georgios N., Poovanna, Likith, Ethiraj, Vinay S., Johansson, Stefan J., Reynolds, Robert G., Heether, Leonard K., Schumann, Tom and Gallagher, Marcus (2013). The Turing test track of the 2012 Mario AI championship: entries and evaluation. 2013 IEEE Conference on Computational Intelligence in Games (CIG), Niagara Falls, ON, Canada, 11-13 August, 2013. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/CIG.2013.6633634
Astronomical catalogue matching as a mixture model problem
Rohde, David, Gallagher, Marcus and Drinkwater, Michael (2012). Astronomical catalogue matching as a mixture model problem. 11th Brazilian Meeting on Bayesian Statistics (EBEB), Amparo, Brazil, 18-22 March 2012. College Park, MD, USA: American Institute of Physics. doi: 10.1063/1.4759615
Beware the parameters: estimation of distribution algorithms applied to circles in a square packing
Gallagher, Marcus (2012). Beware the parameters: estimation of distribution algorithms applied to circles in a square packing. Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Taormina, Italy, 1 - 5 September 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-32964-7_48
Game designers training first person shooter bots
McPartland, Michelle and Gallagher, Marcus (2012). Game designers training first person shooter bots. AI 2012: Advances in Artificial Intelligence, Sydney, Australia, 4 - 7 December 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35101-3_34
Interactively training first person shooter bots
McPartland, Michelle and Gallagher, Marcus (2012). Interactively training first person shooter bots. IEEE International Conference on Computational Intelligence and Games, CIG 2012, Granada, Spain, 11 - 14 September 2012. Piscataway, NJ, United States: IEEE (Institute of Electrical and Electronics Engineers). doi: 10.1109/CIG.2012.6374149
Length scale for characterising continuous optimization problems
Morgan, Rachael and Gallagher, Marcus (2012). Length scale for characterising continuous optimization problems. Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Taormina, Italy, 1 - 5 September 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-32937-1_41
Mishra, Krishna Manjari and Gallagher, Marcus (2012). Variable screening for reduced dependency modelling in Gaussian-based continuous estimation of distribution algorithms. 2012 IEEE World Congress on Computational Intelligence (IEEE-WCCI 2012), Brisbane, QLD Australia, 10-15 June 2012. Piscataway, NJ United States: IEEE. doi: 10.1109/CEC.2012.6256482
Faster and parameter-free discord search in quasi-periodic time series
Luo, Wei and Gallagher, Marcus (2011). Faster and parameter-free discord search in quasi-periodic time series. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Shenzhen, China, 24-27 May 2011. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-20847-8_12
Under voltage load shedding utilizing trajectory sensitivity to enhance voltage stability
Arief, Ardiaty, Nappu, Muhammad Bachtiar, Gallagher, Marcus and Dong, Zhao Yang (2011). Under voltage load shedding utilizing trajectory sensitivity to enhance voltage stability. 21st Australasian Universities Power Engineering Conference (AUPEC) 2011, Brisbane, Australia, 25-28 September 2011. Pitscataway, NJ, United States: IEEE.
Comparison of CPF and modal analysis methods in determining effective DG locations
Arief, Ardiaty, Nappu, Muhammad Bachtiar, Gallagher, Marcus, Dong, Zhao Yang and Zhao, Junhua (2010). Comparison of CPF and modal analysis methods in determining effective DG locations. 9th International Power and Energy Conference (IPEC), Singapore, 27-29 October 2010. United States: IEEE. doi: 10.1109/IPECON.2010.5697057
Unsupervised DRG upcoding detection in healthcare databases
Luo, Wei and Gallagher, Marcus (2010). Unsupervised DRG upcoding detection in healthcare databases. IEEE International Conference on Data Mining, Sydney, NSW, Australia, 14-17 December 2010. Piscataway, NJ, U.S.A.: IEEE Computer Society. doi: 10.1109/ICDMW.2010.108
Luo, Wei, Gallagher, Marcus, O'Kane, Di, Connor, Jason, Dooris, Mark, Roberts, Col, Mortimer, Lachlan and Wiles, Janet (2010). Visualising a state-wide patient data collection: A case study to expand the audience for healthcare data. HIKM 2010: 4th Australasian Workshop on Health Informatics and Knowledge Management, Brisbane, Australia, 18-21 January 2010. Sydney, Australia: Australian Computer Society.
Morgan, Rachael and Gallagher, Marcus (2010). When does dependency modelling help? Using a randomized landscape generator to compare algorithms in terms of problem structure. Parallel Problem Solving from Nature, Kraków, Poland, 11-15 September 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-15844-5_10
An improved small-sample statistical test for comparing the success rates of evolutionary algorithms
Yuan, Bo and Gallagher, Marcus (2009). An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montreal, QC, Canada, 8-12 July 8 2009. New York, NY, United States: ACM. doi: 10.1145/1569901.1570213
Gallagher, Marcus R. (2009). Black-Box Optimization Benchmarking: Results for the BayEDAcGAlgorithm on the Noiseless Function Testbed. New York, NY, USA: Association for Computing Machinery. doi: 10.1145/1570256.1570318
Gallagher, Marcus (2009). Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference (GECCO'09), Montreal, Canada, 8-12 July 2009. New York, United States: ACM Digital Library. doi: 10.1145/1570256.1570332
Convergence analysis of UMDAc with finite populations: A case study on flat landscapes
Yuan, Bo and Gallagher, Marcus (2009). Convergence analysis of UMDAc with finite populations: A case study on flat landscapes. 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montréal, QC, Canada, 8-12 July 2009. New York, NY, U.S.A.: ACM (Association for Computing Machinery) Press. doi: 10.1145/1569901.1569967
Marcus Gallagher (2009). Investigating circles in a square packing problems as a realistic benchmark for continuous metaheuristic optimization algorithms. The VIII Metaheuristic International Conference MIC 2009, Hamburg, Germany, 13-16 July, 2009.
Yeh, F.Y-H. and Gallagher, M. (2008). An empirical study of the sample size variability of optimal active learning using Gaussian process regression. IEEE World Congress on Computational Intelligence, Hong Kong, 1-6 June 2008. Piscataway NJ USA: IEEE. doi: 10.1109/IJCNN.2008.4634342
An influence map model for playing Ms. Pac-Man
Wirth, N. and Gallagher, M. (2008). An influence map model for playing Ms. Pac-Man. IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08), Perth, Australia, 15-18 December 2008. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CIG.2008.5035644
Creating a multi-purpose first person shooter bot with reinforcement learning
McPartland, M. and Gallagher, M. (2008). Creating a multi-purpose first person shooter bot with reinforcement learning. IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08), Perth, Australia, 15-18 December 2008. Piscataway, NJ, U.S.A.: IEEE. doi: 10.1109/CIG.2008.5035633
Kumar, N. and Gallagher, M. (2008). Gaussian mixture models in estimations of distribution algotithms: Implementation details and experimental analysis. 12th Asia-Pacific Symposium on Intelligent and Evolutionary Systems (IES'08), Melbourne, Australia, 7-8 December 2008. Clayton, VIC, Australia: Monash University, Clayton School of Information Technology.
Learning to be a Bot: Reinforcement learning in shooter games
McPartland, M. and Gallagher, M. (2008). Learning to be a Bot: Reinforcement learning in shooter games. 4th Artifical Intelligence for Interactive Digital Entertainment Conference, Stanford, California, 22-24 October, 2008. USA: The AAAI Press.
A comparison of sequence kernels for localization prediction of transmembrane proteins
Maetschke, S., Gallagher, M. and Boden, M. (2007). A comparison of sequence kernels for localization prediction of transmembrane proteins. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology 2007 (CIBCB 2007), Honolulu, Hawaii, 1-5 April 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/cibcb.2007.4221246
An agent based approach to examining shared situation awareness
Connelly, S., Lindsay, P. A. and Gallagher, M. (2007). An agent based approach to examining shared situation awareness. 12th IEEE International Conference on Engineering Complex Computer Systems (ICECCS 2007), Auckland, New Zealand, 11-14 July 2007. Los Alamitos, CA, U.S.A.: IEEE Computer Society. doi: 10.1109/ICECCS.2007.14
Bayesian inference in estimation of distribution algorithms
Gallagher, M. R., Wood, I., Keith, J. and Sofronov, G. (2007). Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (CEC 2007), Singapore, 25-28 September 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2007.4424463
Combining Meta-EAs and racing for difficult EA parameter tuning tasks
Yuan, Bo and Gallagher, Marcus (2007). Combining Meta-EAs and racing for difficult EA parameter tuning tasks. Workshop on Parameter Setting in Genetic and Evolutionary Algorithms, Washington Dc, 2005. BERLIN: SPRINGER-VERLAG BERLIN.
Evolving pac-man players: Can we learn from raw input?
Gallagher, M. and Ledwich, M. (2007). Evolving pac-man players: Can we learn from raw input?. 2007 IEEE Symposium Series on Computational Intelligence and Games (IEEE SSCI 2007), Honolulu, Hawaii, 1-5 April, 2007. United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/CIG.2007.368110
A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA
Yuan, Bo and Gallagher, Marcus (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation, CEC 2006, , , July 16, 2006-July 21, 2006.
A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA
Gallagher, M. R. and Yuan, B. (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, Canada, 16-21 July 2006. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2006.1688497
Higher order HMMs for localization prediction of transmembrance proteins
Maetschke, S. R., Boden, M B and Gallagher, M R (2006). Higher order HMMs for localization prediction of transmembrance proteins. 2006 Workshop on Intelligent Systems for Bioinformatics (WISB 2006), Hobart, Australia, 4 December, 2006. New South Wales, Australia: Australian Computer Society Inc..
A hybrid approach to parameter tuning in genetic algorithms
Yuan, Bo and Gallagher, Marcus (2005). A hybrid approach to parameter tuning in genetic algorithms. 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005, , , September 2, 2005-September 5, 2005.
Yuan, Bo and Gallagher, Marcus (2005). Experimental results for the special session on real-parameter optimization at CEC 2005: A simple, continuous EDA. 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005, , , September 2, 2005-September 5, 2005.
A hybrid approach to parameter tuning in genetic algorithms
Yuan, B. and Gallagher, M. R. (2005). A hybrid approach to parameter tuning in genetic algorithms. 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005), Edinburgh, Scotland, 2-5 September 2005. U.S.A.: IEEE.
An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification
Yeh, Y. and Gallagher, M. R. (2005). An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification. Intelligent Data Engineering and Automated Learning - IDEAL205, Brisbane, Australia, 6-8 July, 2005. Berlin, Germany: Springer. doi: 10.1007/11508069_29
Yuan, B. and Gallagher, M. R. (2005). Experimental results for the special session on real-parameter optimization at CEC 2005: A Simple, Continuous EDA. 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005), Edinburgh, Scotland, 2-5 September, 2005. U.S.A.: IEEE.
Yuan, B., Gallagher, M. R. and Crozier, S. (2005). MRI magnet design: Search space analysis, EDAs and a real-world problem with significant dependencies. 7th Annual Genetic and Evolutionary Computation Conference - GELCCO 2005, Washington DC, USA, 25-29 June, 2005. New York, USA: ACM Press. doi: 10.1145/1068009.1068362
On the importance of diversity maintenance in estimation of distribution algorithms
Yuan, B. and Gallagher, M. R. (2005). On the importance of diversity maintenance in estimation of distribution algorithms. 7th Annual Genetic and Evolutionary Computation Conference GECCO 2005, Washington DC, USA, 25-29 June, 2005. New York, USA: ACM Press. doi: 10.1145/1068009.1068129
Machine learning for matching astronomy catalogues
Rohde, D. J., Drinkwater, M. J., Gallagher, M. R., Downs, T. and Doyle, M. T. (2004). Machine learning for matching astronomy catalogues. The Fifth International Intelligent Data Engineering and Automated Learning Conference (IDEAL 2004), Exeter, U.K., 25-27 August 2004. Berlin, Germany: Springer.
Statistical racing techniques for improved empirical evaluation of evolutionary algorithms
Yuan, B. and Gallagher, M. R. (2004). Statistical racing techniques for improved empirical evaluation of evolutionary algorithms. The Eighth International Conference on Parallel Problem Solving from Nature, Birmingham, U.K., 18-22 September 2004. Berlin: Springer-Verlag.
Blind separation of noisy mixtures using the SAND algorithm
Leong, W. Y., Homer, J. P. and Gallagher, M. R. (2003). Blind separation of noisy mixtures using the SAND algorithm. The Seventh International Symposium on DSP for Communication System and the Second Workshop on the Internet, Telecommunication and Signal Processing, Coolangatta, 8-11 Decmber, 2003. Wollongong: The University of Wollongong.
Learning to play Pac-Man: An evolutionary, rule-based approach
Gallagher, M. R. and Ryan, A. J. (2003). Learning to play Pac-Man: An evolutionary, rule-based approach. The 2003 Congress on Evolutionary Computation (CEC 2003), Canberra, Australia, 8-12 December 2003. Piscataway, NJ, U.S.A.: The Institute of Electrical and Electronics Engineers. doi: 10.1109/CEC.2003.1299397
Yuan, B. and Gallagher, M. R. (2003). On building a principled framework for evaluating and testing evolutionary algorithms: A continuous landscape generator. The 2003 Congress on Evolutionary Computation (CEC '03), Canberra, Australia, 8-12 December 2003. Piscataway, NJ, U.S.A.: The Institute of Electrical and Electronics Engineers. doi: 10.1109/CEC.2003.1299610
Playing in continuous spaces: Some analysis and extension of population-based incremental learning
Yuan, B. and Gallagher, M. R. (2003). Playing in continuous spaces: Some analysis and extension of population-based incremental learning. 2003 Congress on Evolutionary Computation (CEC '03), Canberra, Australia, 8-12 December 2003. Piscataway, NJ, U.S.A.: The Institute of Electrical and Electronics Engineers. doi: 10.1109/CEC.2003.1299609
Neural networks and the classification of mineralogical samples using x-ray spectra
Gallagher, M. R. and Deacon, P. (2002). Neural networks and the classification of mineralogical samples using x-ray spectra. Ninth International Conference on Neural Information Processing, Singapore, 18-22 November, 2002. Piscataway, NJ: The Institute of Electrical and Electronics Engineers. doi: 10.1109/ICONIP.2002.1201983
Gallagher, Marcus (2001). Fitness distance correlation of neural network error surfaces: A scalable, continuous optimization problem. Springer Verlag.
Gallagher, M. R. (2001). Fitness distance correlation of neural network error surfaces: A scalable, continuous optimization problem. Twelfth European Conference on Machine Learning, Freiburg, Germany, 3-7 September, 2001. Berlin: Springer-Verlag.
An empirical investigation of the user-parameters and performance of continuous PBIL algorithms
Gallagher, M. R. (2000). An empirical investigation of the user-parameters and performance of continuous PBIL algorithms. NNSP 2000, Sydney, NSW Australia, 11-13 December 2000. Piscataway, NJ United States: IEEE. doi: 10.1109/nnsp.2000.890149
Real-valued evolutionary optimization using a flexible probability density estimator
Gallagher, M., Frean, M. and Downs, T. (1999). Real-valued evolutionary optimization using a flexible probability density estimator. GECCO-99, Orlando, Florida, 13-17 July, 1999. San Francisco: Morgan Kaufmann Publishers.
Embedded HF frequency management system
Ripley, M. W., Darnell, M. and Gallagher, M. (1996). Embedded HF frequency management system. IEE.
Flexible, low-cost, ionospheric sounding system
Bartlett, A., Darnell, M. and Gallagher, M. (1996). Flexible, low-cost, ionospheric sounding system. IEE.
Passive monitoring for improved HF frequency management
Piggin, P. W., Darnell, M. and Gallagher, M. (1996). Passive monitoring for improved HF frequency management. IEE.
Channel evaluation from predicted zero crossing analysis
Piggin, P. W. and Gallagher, M. (1995). Channel evaluation from predicted zero crossing analysis. IEEE.
HF DSP based frequency management system
Ripley, M., Gallagher, M. and Darnell, M. (1995). HF DSP based frequency management system. Proceeding of the 6th International Conference on Radio Receivers and Associated Systems, , , September 26, 1995-September 27, 1995. IEE.
Spectrally efficient oblique ionospheric sounding
Bartlett, A., Gallagher, M. and Darnell, M. (1995). Spectrally efficient oblique ionospheric sounding. IEE.
Advanced radio system architectures to integrate network and frequency management
Gallagher, M., Bennett, S. A.W., Darnell, M. and Honary, B. (1994). Advanced radio system architectures to integrate network and frequency management. Publ by IEE.
Dual ionospheric sounding system monitor for HF RTCE
Ripley, M., Gallagher, M. and Darnell, M. (1994). Dual ionospheric sounding system monitor for HF RTCE. Publ by IEE.
Extraction, analysis and interpretation of digital ionograms
Bartlett, A., Gallagher, M. and Darnell, M. (1994). Extraction, analysis and interpretation of digital ionograms. Publ by IEE.
In-band multi-user transmission schemes for HF communications
Quirke, T. M., Yung, H. M., Darnell, M. and Gallagher, M. (1994). In-band multi-user transmission schemes for HF communications. Publ by IEE.
Gallagher, M., Darnell, M. and Clark, P. (1991). Architectural considerations for adaptive digital signal processing within long-range radio communication system terminals. Publ by IEE.
Economic ionospheric sounding system using standard HF radio system elements
Gallagher, M. and Darnell, M. (1991). Economic ionospheric sounding system using standard HF radio system elements. Publ by IEE.
Propagation and interference measurements for use in real-time frequency management
Gallagher, M. and Darnell, M. (1991). Propagation and interference measurements for use in real-time frequency management. Publ by IEE.
Simple model of intermodulation spectra for use on a personal computer
Riley, N. G., Gallagher, M. and Prasad, K. V. (1990). Simple model of intermodulation spectra for use on a personal computer. Publ by IEE.
Synchronisation techniques for dispersive time-variable channels
Honary, B., Darnell, M., Zolghadr, F. and Gallagher, M. (1990). Synchronisation techniques for dispersive time-variable channels. Publ by IEE.
International Journal of Neural Systems
International Journal of Neural Systems. (2006). 16 (5)
Intelligent Data Engineering and Automated Learning - IDEAL2005
Marcus Gallagher, James Hogan and Frederic Maire eds. (2005). Intelligent Data Engineering and Automated Learning - IDEAL2005. 6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005: Lecture Notes in Computer Science (journal), Brisbane, Australia, 6-8 July 2005. Germany: Springer.
Gallagher, M. R. (2005). McCulloch-Pitts Network.
Gallagher, M. R. (2005). Perceptron.
Multi-layer perceptron error surfaces : visualization, structure and modelling
Gallagher, Marcus Reginald (2000). Multi-layer perceptron error surfaces : visualization, structure and modelling. PhD Thesis, Computer Science and Electrical Engineering, The University of Queensland. doi: 10.14264/157842
(2021–2022) University of Melbourne
Machine Learning for Automated Network Anomaly Detection, Cyber Security and Analysis - Phase II
(2019) Innovation Connections
Machine Learning for Automated Network Anomaly detection and Analysis
(2018–2019) Innovation Connections
Active and interactive analysis of prescription data for harm minimisation
(2016–2020) ARC Linkage Projects
(2013–2016) ARC Linkage Projects
Data Mining Applications in the Regulation of Prescription Opioids
(2011–2013) Queensland Health
Understanding Patient Flow Bottlenecks and Patterns from Hospital Information Systems Data
(2010–2012) UQ Collaboration and Industry Engagement Fund
Detecting and Understanding Dysfunctional Anomalies in Queensland Healthcare Databases
(2008–2011) ARC Linkage Projects
Metaheuristic Algorithms for Realistic Optimization Problems
(2007–2009) UQ Early Career Researcher
(2005–2007) ARC Linkage Projects
Smart Astronomy: Using Computational Science To Understand Distant Radio Galaxies
(2005–2006) ARC Special Research Initiatives - E-Research
The Application of Machine Learning Techniques in Predicting Medical Outcomes
(2005–2006) UQ FirstLink Scheme
Population-based optimization algorithms and probabilistic modelling
(2001) UQ New Staff Research Start-Up Fund
Improving neuroevolution using ideas from deep learning and optimization
Doctor Philosophy — Principal Advisor
Other advisors:
Fitness Landscape Features as Curriculum Ordering Measures for Reinforcement Learning
Doctor Philosophy — Principal Advisor
Generating data-driven continuous optimization problems for benchmarking
Doctor Philosophy — Principal Advisor
Other advisors:
Adaptive Curriculums for Robotic Reinforcement Learning
Doctor Philosophy — Principal Advisor
Multi-objective optimisation and multi-agent learning for IoT devices.
Doctor Philosophy — Principal Advisor
Other advisors:
Investigating the use of Computer Vision Techniques for Analysing the Surf Zone
Doctor Philosophy — Associate Advisor
Other advisors:
Approaches to scalable, sustainable, and ethical natural language processing research in the face of rapid development
Doctor Philosophy — Associate Advisor
Other advisors:
Characterizing Influence and Sensitivity in the Interpolating Regime
Doctor Philosophy — Associate Advisor
Other advisors:
Medical Image Segmentation with Limited Annotated Data
Doctor Philosophy — Associate Advisor
Other advisors:
Towards Autonomous Network Security
Doctor Philosophy — Associate Advisor
Other advisors:
Parsimony and Performance in Rule-Based Evolutionary Reinforcement Learning
(2023) Doctor Philosophy — Principal Advisor
Discounting-free Policy Gradient Reinforcement Learning from Transient States
(2022) Doctor Philosophy — Principal Advisor
Other advisors:
(2021) Doctor Philosophy — Principal Advisor
Other advisors:
Stochaskell: A common platform for probabilistic programming research and applications
(2021) Master Philosophy — Principal Advisor
Other advisors:
Results on Infinitely Wide Multi-layer Perceptrons
(2020) Doctor Philosophy — Principal Advisor
Other advisors:
Analysing and Comparing Problem Landscapes for Black-Box Optimization via Length Scale
(2015) Doctor Philosophy — Principal Advisor
(2015) Doctor Philosophy — Principal Advisor
Other advisors:
(2014) Doctor Philosophy — Principal Advisor
Advanced Computational Methods for System Voltage Stability Enhancement
(2013) Doctor Philosophy — Principal Advisor
(2013) Doctor Philosophy — Principal Advisor
(2010) Master Philosophy — Principal Advisor
Optimal active learning: experimental factors and membership query learning
(2010) Doctor Philosophy — Principal Advisor
Other advisors:
Kinematic and Elasto-Dynamic Design Optimisation of a Class of Parallel Kinematic Machines
(2009) Doctor Philosophy — Principal Advisor
The Development and Application of Statistical and Machine Learning Techniques in Probabilistic Astronomical Catalogue-Matching Problems
(2009) Doctor Philosophy — Principal Advisor
TOPOLOGICAL MODELS OF TRANSMEMBRANE PROTEINS FOR SUBCELLULAR LOCALIZATION PREDICTION
() Doctor Philosophy — Principal Advisor
Other advisors:
TOWARDS IMPROVED EXPERIMENTAL EVALUATION AND COMPARISON OF EVOLUTIONARY ALGORITHMS
(2006) Doctor Philosophy — Principal Advisor
Graph Representation Learning for Cyberattack Detection and Forensics
(2023) Master Philosophy — Associate Advisor
Other advisors:
The Detection of Network Cyber Attacks Using Machine Learning
(2023) Doctor Philosophy — Associate Advisor
Other advisors:
Efficient second-order optimisation methods for large scale machine learning
(2022) Doctor Philosophy — Associate Advisor
Other advisors:
Smart Deployment of Community Energy Storage in Power Grid with PV Units
(2018) Doctor Philosophy — Associate Advisor
Other advisors:
Biometric Markers for Affective Disorders
(2015) Doctor Philosophy — Associate Advisor
Other advisors:
Large Scale Material Science Data Analysis
(2015) Master Philosophy — Associate Advisor
Other advisors:
Making the most of machine learning and freely available datasets: A deforestation case study
(2015) Doctor Philosophy — Associate Advisor
Other advisors:
(2015) Doctor Philosophy — Associate Advisor
Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging
(2015) Master Philosophy — Associate Advisor
Estimation of Distribution Algorithms for Single- and Multi-Objective Optimization
(2014) Doctor Philosophy — Associate Advisor
Other advisors:
Group-based Classification with an Application in Cervical Cancer Screening
(2014) Doctor Philosophy — Associate Advisor
Machine Learning as an Adjunct to Clinical Decision Making in Alcohol Dependence Treatment
(2014) Doctor Philosophy — Associate Advisor
Other advisors:
Heuristic algorithms for graph decomposition problems
(2009) Master Philosophy — Associate Advisor
Adaptation by prediction: Reading the play in robot soccer
(2008) Doctor Philosophy — Associate Advisor
Visual Learning for Mobile Robot Localisation
(2008) Doctor Philosophy — Associate Advisor
Implementing blind source separation in signal processing and telecommunications
(2006) Doctor Philosophy — Associate Advisor
Application of the Tree Augmented Naive Bayes Network to Classification and Forecasting
(2005) Doctor Philosophy — Associate Advisor
THE NATURE OF CHANGE IN COMPLEX, SOCIO-TECHNICAL SYSTEMS
(2005) Doctor Philosophy — Associate Advisor
FAST LEARNING IN BOLTZMANN MACHINES
(2004) Doctor Philosophy — Associate Advisor