The University of Queensland

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

Benchmarking the benchmark — Comparing synthetic and real-world Network IDS datasets

Layeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2024). Benchmarking the benchmark — Comparing synthetic and real-world Network IDS datasets. Journal of Information Security and Applications, 80 103689, 1-18. doi: 10.1016/j.jisa.2023.103689

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

An agile new research framework for hybrid human-AI teaming: trust, transparency, and transferability

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

Predicting alcohol dependence treatment outcomes: A prospective comparative study of clinical psychologists vs ‘trained’ machine learning models

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

Machine learning vs addiction therapists: a pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication

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

Parallel evolutionary algorithm for single and multi-objective optimisation: Differential evolution and constraints handling

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

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

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

Sampling techniques and distance metrics in high dimensional continuous landscape analysis: limitations and improvements

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

Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators

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

Using landscape topology to compare continuous metaheuristics: a framework and case study on EDAs and ridge structure

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

Introduction

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. GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, 15-19 July 2023. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3583133.3590648

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

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

An Implementation and Experimental Evaluation of a Modularity Explicit Encoding Method for Neuroevolution on Complex Learning Tasks

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

Flood-fill Q-learning updates for learning redundant policies in order to interact with a computer screen by clicking

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.

Exploratory analysis of clustering problems using a comparison of particle swarm optimization and differential evolution

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

Variable screening for reduced dependency modelling in Gaussian-based continuous estimation of distribution algorithms

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

Visualising a state-wide patient data collection: A case study to expand the audience for healthcare data

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.

When does dependency modelling help? Using a randomized landscape generator to compare algorithms in terms of problem structure

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

Black-Box Optimization Benchmarking: Results for the BayEDAcGAlgorithm on the Noiseless Function Testbed

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

Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed

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

Investigating circles in a square packing problems as a realistic benchmark for continuous metaheuristic optimization algorithms

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.

An empirical study of the sample size variability of optimal active learning using Gaussian process regression

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

Gaussian mixture models in estimations of distribution algotithms: Implementation details and experimental analysis

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.

Experimental results for the special session on real-parameter optimization at CEC 2005: A simple, continuous EDA

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

Experimental results for the special session on real-parameter optimization at CEC 2005: A Simple, Continuous EDA

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.

MRI magnet design: Search space analysis, EDAs and a real-world problem with significant dependencies

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

On building a principled framework for evaluating and testing evolutionary algorithms: A continuous landscape generator

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

Fitness distance correlation of neural network error surfaces: A scalable, continuous optimization problem

Gallagher, Marcus (2001). Fitness distance correlation of neural network error surfaces: A scalable, continuous optimization problem. Springer Verlag.

Fitness distance correlation of neural network error surfaces: A scalable, continuous optimization problem

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.

Architectural considerations for adaptive digital signal processing within long-range radio communication system terminals

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.

McCulloch-Pitts Network

Gallagher, M. R. (2005). McCulloch-Pitts Network.

Perceptron

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, School of Computer Science and Electrical Engineering, The University of Queensland. doi: 10.14264/157842