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Marcus Gallagher
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- affiliation: University of Queensland, School of Information Technology and Electrical Engineering, St. Lucia, QLD, Australia
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2020 – today
- 2024
- [j26]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann:
Feature extraction for machine learning-based intrusion detection in IoT networks. Digit. Commun. Networks 10(1): 205-216 (2024) - [j25]Siamak Layeghy, Marcus Gallagher, Marius Portmann:
Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets. J. Inf. Secur. Appl. 80: 103689 (2024) - [c63]Marcus Gallagher, Mario A. Muñoz:
Towards an Improved Understanding of Features for More Interpretable Landscape Analysis. GECCO Companion 2024: 135-138 - [c62]Sara Hajari, Marcus Gallagher:
Searching for Benchmark Problem Instances from Data-Driven Optimisation. GECCO Companion 2024: 139-142 - [c61]Yukai Qiao, Marcus Gallagher:
Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. GECCO Companion 2024: 1520-1526 - [i21]Yukai Qiao, Marcus Gallagher:
Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. CoRR abs/2407.08335 (2024) - 2023
- [j24]Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann:
From zero-shot machine learning to zero-day attack detection. Int. J. Inf. Sec. 22(4): 947-959 (2023) - [j23]Jacob Schrum, Jialin Liu, Cameron Browne, Anikó Ekárt, Marcus Gallagher:
Guest Editorial: Special Issue on Evolutionary Computation for Games. IEEE Trans. Games 15(1): 1-4 (2023) - [c60]Yukai Qiao, Marcus Gallagher:
Modularity Based Linkage Model For Neuroevolution. GECCO Companion 2023: 675-678 - [c59]Humphrey Munn, Marcus Gallagher:
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. IJCNN 2023: 1-7 - [i20]Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning Policies. CoRR abs/2305.09922 (2023) - [i19]Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCS. CoRR abs/2305.09945 (2023) - [i18]Yukai Qiao, Marcus Gallagher:
Modularity based linkage model for neuroevolution. CoRR abs/2306.01227 (2023) - 2022
- [j22]Sobia Saleem, Marcus Gallagher:
Using regression models for characterizing and comparing black box optimization problems. Swarm Evol. Comput. 68: 100981 (2022) - [j21]Sabrina B. Caldwell, Penny Sweetser, Nicholas O'Donnell, Matthew James Knight, Matthew Aitchison, Tom Gedeon, Daniel Johnson, Margot Brereton, Marcus Gallagher, David Conroy:
An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability. ACM Trans. Interact. Intell. Syst. 12(3): 17:1-17:36 (2022) - [c58]Vektor Dewanto, Marcus Gallagher:
Examining Average and Discounted Reward Optimality Criteria in Reinforcement Learning. AI 2022: 800-813 - [c57]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. DSC 2022: 1-9 - [c56]Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. GECCO 2022: 323-331 - [c55]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. NOMS 2022: 1-9 - [i17]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. CoRR abs/2201.07537 (2022) - [i16]Vektor Dewanto, Marcus Gallagher:
Approximate discounting-free policy evaluation from transient and recurrent states. CoRR abs/2204.04324 (2022) - [i15]Humphrey Munn, Marcus Gallagher:
Modularity in NEAT Reinforcement Learning Networks. CoRR abs/2205.06451 (2022) - 2021
- [c54]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. AAAI 2021: 9967-9977 - [c53]Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. GECCO Companion 2021: 1630-1638 - [i14]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. CoRR abs/2103.16329 (2021) - [i13]Siamak Layeghy, Marcus Gallagher, Marius Portmann:
Benchmarking the Benchmark - Analysis of Synthetic NIDS Datasets. CoRR abs/2104.09029 (2021) - [i12]Vektor Dewanto, Marcus Gallagher:
A nearly Blackwell-optimal policy gradient method. CoRR abs/2105.13609 (2021) - [i11]Vektor Dewanto, Marcus Gallagher:
Examining average and discounted reward optimality criteria in reinforcement learning. CoRR abs/2107.01348 (2021) - [i10]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann:
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks. CoRR abs/2108.12722 (2021) - [i9]Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann:
From Zero-Shot Machine Learning to Zero-Day Attack Detection. CoRR abs/2109.14868 (2021) - 2020
- [j20]Helen Mayfield, Carl S. Smith, Marcus Gallagher, Marc Hockings:
Considerations for selecting a machine learning technique for predicting deforestation. Environ. Model. Softw. 131: 104741 (2020) - [j19]Xuelei Hu, Marcus Gallagher, William Loveday, Abhilash Dev, Jason P. Connor:
Network Analysis and Visualisation of Opioid Prescribing Data. IEEE J. Biomed. Health Informatics 24(5): 1447-1455 (2020) - [c52]Yukai Qiao, Marcus Gallagher:
An Implementation and Experimental Evaluation of a Modularity Explicit Encoding Method for Neuroevolution on Complex Learning Tasks. Australasian Conference on Artificial Intelligence 2020: 138-149 - [c51]Saskia Van Ryt, Marcus Gallagher, Ian A. Wood:
A Novel Mutation Operator for Variable Length Algorithms. Australasian Conference on Artificial Intelligence 2020: 176-188 - [c50]Jordan T. Bishop, Marcus Gallagher:
Optimality-Based Analysis of XCSF Compaction in Discrete Reinforcement Learning. PPSN (2) 2020: 471-484 - [c49]Nathaniel du Preez-Wilkinson, Marcus Gallagher:
Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces. PPSN (2) 2020: 500-514 - [e2]Marcus Gallagher, Nour Moustafa, Erandi Lakshika:
AI 2020: Advances in Artificial Intelligence - 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29-30, 2020, Proceedings. Lecture Notes in Computer Science 12576, Springer 2020, ISBN 978-3-030-64983-8 [contents] - [i8]Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher:
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. CoRR abs/2002.08517 (2020) - [i7]Jordan T. Bishop, Marcus Gallagher:
Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning. CoRR abs/2009.01476 (2020) - [i6]Vektor Dewanto, George Dunn, Ali Eshragh, Marcus Gallagher, Fred Roosta:
Average-reward model-free reinforcement learning: a systematic review and literature mapping. CoRR abs/2010.08920 (2020)
2010 – 2019
- 2019
- [j18]Sobia Saleem, Marcus Gallagher, Ian A. Wood:
Direct Feature Evaluation in Black-Box Optimization Using Problem Transformations. Evol. Comput. 27(1): 75-98 (2019) - [j17]Kenichi Tamura, Marcus Gallagher:
Quantitative measure of nonconvexity for black-box continuous functions. Inf. Sci. 476: 64-82 (2019) - [c48]David A. Roberts, Marcus Gallagher, Thomas Taimre:
Reversible Jump Probabilistic Programming. AISTATS 2019: 634-643 - [c47]Marcus Gallagher:
Fitness Landscape Analysis in Data-Driven Optimization: An Investigation of Clustering Problems. CEC 2019: 2308-2314 - [c46]Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud:
Exploring the MLDA benchmark on the nevergrad platform. GECCO (Companion) 2019: 1888-1896 - [c45]Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher:
Exchangeability and Kernel Invariance in Trained MLPs. IJCAI 2019: 3592-3598 - [i5]Russell Tsuchida, Fred Roosta, Marcus Gallagher:
Richer priors for infinitely wide multi-layer perceptrons. CoRR abs/1911.12927 (2019) - 2018
- [j16]Peter A. N. Bosman, Marcus Gallagher:
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 Comput. 22(4): 1209-1223 (2018) - [c44]Nathaniel du Preez-Wilkinson, Marcus Gallagher, Xuelei Hu:
Intra-task Curriculum Learning for Faster Reinforcement Learning in Video Games. Australasian Conference on Artificial Intelligence 2018: 65-70 - [c43]Nathaniel du Preez-Wilkinson, Marcus Gallagher, Xuelei Hu:
Flood-Fill Q-Learning Updates for Learning Redundant Policies in Order to Interact with a Computer Screen by Clicking. Australasian Conference on Artificial Intelligence 2018: 537-542 - [c42]Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher:
Invariance of Weight Distributions in Rectified MLPs. ICML 2018: 5002-5011 - [c41]Sobia Saleem, Marcus Gallagher, Ian A. Wood:
A Model-Based Framework for Black-Box Problem Comparison Using Gaussian Processes. PPSN (2) 2018: 284-295 - [c40]Robin C. Purshouse, Christine Zarges, Sylvain Cussat-Blanc, Michael G. Epitropakis, Marcus Gallagher, Thomas Jansen, Pascal Kerschke, Xiaodong Li, Fernando G. Lobo, Julian F. Miller, Pietro S. Oliveto, Mike Preuss, Giovanni Squillero, Alberto Paolo Tonda, Markus Wagner, Thomas Weise, Dennis Wilson, Borys Wróbel, Ales Zamuda:
Workshops at PPSN 2018. PPSN (2) 2018: 490-497 - [i4]Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher:
Exchangeability and Kernel Invariance in Trained MLPs. CoRR abs/1810.08351 (2018) - 2017
- [j15]Dorival M. Pedroso, Mohammad Reza Bonyadi, Marcus Gallagher:
Parallel evolutionary algorithm for single and multi-objective optimisation: Differential evolution and constraints handling. Appl. Soft Comput. 61: 995-1012 (2017) - [j14]Helen Mayfield, Carl S. Smith, Marcus Gallagher, Marc Hockings:
Use of freely available datasets and machine learning methods in predicting deforestation. Environ. Model. Softw. 87: 17-28 (2017) - [j13]Rachael Morgan, Marcus Gallagher:
Analysing and characterising optimization problems using length scale. Soft Comput. 21(7): 1735-1752 (2017) - [c39]Sobia Saleem, Marcus Gallagher:
Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution. ACALCI 2017: 314-325 - [i3]Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher:
Invariance of Weight Distributions in Rectified MLPs. CoRR abs/1711.09090 (2017) - 2016
- [j12]Marcus Gallagher:
Towards improved benchmarking of black-box optimization algorithms using clustering problems. Soft Comput. 20(10): 3835-3849 (2016) - 2015
- [c38]Xuelei Hu, Marcus Gallagher, William Loveday, Jason P. Connor, Janet Wiles:
Detecting Anomalies in Controlled Drug Prescription Data Using Probabilistic Models. ACALCI 2015: 337-349 - [i2]Dimitri Klimenko, Hanna Kurniawati, Marcus Gallagher:
A Stochastic Process Model of Classical Search. CoRR abs/1511.08574 (2015) - 2014
- [j11]Wei Luo, Marcus Gallagher, Bill Loveday, Susan Ballantyne, Jason P. Connor, Janet Wiles:
Detecting contaminated birthdates using generalized additive models. BMC Bioinform. 15: 185 (2014) - [j10]Rachael Morgan, Marcus Gallagher:
Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements. IEEE Trans. Evol. Comput. 18(3): 456-461 (2014) - [c37]Krishna Manjari Mishra, Marcus Gallagher:
A Modified Screening Estimation of Distribution Algorithm for Large-Scale Continuous Optimization. SEAL 2014: 119-130 - [c36]Marcus Gallagher:
Clustering Problems for More Useful Benchmarking of Optimization Algorithms. SEAL 2014: 131-142 - [c35]Rachael Morgan, Marcus Gallagher:
Fitness Landscape Analysis of Circles in a Square Packing Problems. SEAL 2014: 455-466 - 2013
- [j9]Wei Luo, Marcus Gallagher, Janet Wiles:
Parameter-Free Search of Time-Series Discord. J. Comput. Sci. Technol. 28(2): 300-310 (2013) - [c34]Noor Shaker, Julian Togelius, Georgios N. Yannakakis, Likith Poovanna, Vinay Sudha Ethiraj, Stefan J. Johansson, Robert G. Reynolds, Leonard Kinnaird-Heether, Tom Schumann, Marcus Gallagher:
The turing test track of the 2012 Mario AI Championship: Entries and evaluation. CIG 2013: 1-8 - 2012
- [j8]R. Morgan, Marcus Gallagher:
Using Landscape Topology to Compare Continuous Metaheuristics: A Framework and Case Study on EDAs and Ridge Structure. Evol. Comput. 20(2): 277-299 (2012) - [j7]Ling Chen, Yang Liu, Marcus Gallagher, Bernard Pailthorpe, Shazia W. Sadiq, Heng Tao Shen, Xue Li:
Introducing Cloud Computing Topics in Curricula. J. Inf. Syst. Educ. 23(3): 315-324 (2012) - [c33]Michelle McPartland, Marcus Gallagher:
Game Designers Training First Person Shooter Bots. Australasian Conference on Artificial Intelligence 2012: 397-408 - [c32]Krishna Manjari Mishra, Marcus Gallagher:
Variable screening for reduced dependency modelling in Gaussian-based continuous Estimation of Distribution Algorithms. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c31]Michelle McPartland, Marcus Gallagher:
Interactively training first person shooter bots. CIG 2012: 132-138 - [c30]Rachael Morgan, Marcus Gallagher:
Length Scale for Characterising Continuous Optimization Problems. PPSN (1) 2012: 407-416 - [c29]Marcus Gallagher:
Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing. PPSN (2) 2012: 478-487 - 2011
- [j6]Michelle McPartland, Marcus Gallagher:
Reinforcement Learning in First Person Shooter Games. IEEE Trans. Comput. Intell. AI Games 3(1): 43-56 (2011) - [c28]Wei Luo, Marcus Gallagher:
Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series. PAKDD (2) 2011: 135-148 - 2010
- [j5]Liwen You, Vladimir Brusic, Marcus Gallagher, Mikael Bodén:
Using Gaussian Process with Test Rejection to Detect T-Cell Epitopes in Pathogen Genomes. IEEE ACM Trans. Comput. Biol. Bioinform. 7(4): 741-751 (2010) - [c27]Wei Luo, Marcus Gallagher:
Unsupervised DRG Upcoding Detection in Healthcare Databases. ICDM Workshops 2010: 600-605 - [c26]Rachael Morgan, Marcus Gallagher:
When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure. PPSN (1) 2010: 94-103
2000 – 2009
- 2009
- [c25]Bo Yuan, Marcus Gallagher:
Convergence analysis of UMDAC with finite populations: a case study on flat landscapes. GECCO 2009: 477-482 - [c24]Bo Yuan, Marcus Gallagher:
An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. GECCO 2009: 1879-1880 - [c23]Marcus Gallagher:
Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. GECCO (Companion) 2009: 2281-2286 - [c22]Marcus R. Gallagher:
Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noisy function testbed. GECCO (Companion) 2009: 2383-2388 - 2008
- [c21]Michelle McPartland, Marcus Gallagher:
Learning to be a Bot: Reinforcement Learning in Shooter Games. AIIDE 2008 - [c20]Michelle McPartland, Marcus Gallagher:
Creating a multi-purpose first person shooter bot with reinforcement learning. CIG 2008: 143-150 - [c19]Nathan Wirth, Marcus Gallagher:
An influence map model for playing Ms. Pac-Man. CIG 2008: 228-233 - [c18]Flora Yu-Hui Yeh, Marcus Gallagher:
An empirical study of the sample size variability of optimal active learning using Gaussian process regression. IJCNN 2008: 3787-3794 - 2007
- [c17]Marcus Gallagher, Ian A. Wood, Jonathan M. Keith, George Y. Sofronov:
Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2007: 127-133 - [c16]Stefan Maetschke, Marcus Gallagher, Mikael Bodén:
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. CIBCB 2007: 367-372 - [c15]Marcus Gallagher, Mark Ledwich:
Evolving Pac-Man Players: Can We Learn from Raw Input? CIG 2007: 282-287 - [c14]Simon Connelly, Peter A. Lindsay, Marcus Gallagher:
An agent based approach to examining shared situation awareness. ICECCS 2007: 138-147 - [p1]Bo Yuan, Marcus Gallagher:
Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks. Parameter Setting in Evolutionary Algorithms 2007: 121-142 - 2006
- [j4]Marcus Gallagher, Bo Yuan:
A general-purpose tunable landscape generator. IEEE Trans. Evol. Comput. 10(5): 590-603 (2006) - [c13]Bo Yuan, Marcus Gallagher:
A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. IEEE Congress on Evolutionary Computation 2006: 1585-1591 - [i1]Marcus Gallagher, Bo Yuan:
A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. Theory of Evolutionary Algorithms 2006 - 2005
- [j3]Marcus Gallagher, Marcus R. Frean:
Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. Evol. Comput. 13(1): 29-42 (2005) - [c12]Bo Yuan, Marcus Gallagher:
A hybrid approach to parameter tuning in genetic algorithms. Congress on Evolutionary Computation 2005: 1096-1103 - [c11]Bo Yuan, Marcus Gallagher:
Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA. Congress on Evolutionary Computation 2005: 1792-1799 - [c10]Bo Yuan, Marcus Gallagher:
On the importance of diversity maintenance in estimation of distribution algorithms. GECCO 2005: 719-726 - [c9]Bo Yuan, Marcus Gallagher, Stuart Crozier:
MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. GECCO 2005: 2141-2148 - [c8]Flora Yu-Hui Yeh, Marcus Gallagher:
An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification. IDEAL 2005: 220-227 - [e1]Marcus Gallagher, James M. Hogan, Frédéric Maire:
Intelligent Data Engineering and Automated Learning - IDEAL 2005, 6th International Conference, Brisbane, Australia, July 6-8, 2005, Proceedings. Lecture Notes in Computer Science 3578, Springer 2005, ISBN 3-540-26972-X [contents] - 2004
- [c7]David Rohde, Michael Drinkwater, Marcus Gallagher, Tom Downs, Marianne Doyle:
Machine Learning for Matching Astronomy Catalogues. IDEAL 2004: 702-707 - [c6]Bo Yuan, Marcus Gallagher:
Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. PPSN 2004: 172-181 - 2003
- [j2]Marcus Gallagher, Tom Downs:
Visualization of learning in multilayer perceptron networks using principal component analysis. IEEE Trans. Syst. Man Cybern. Part B 33(1): 28-34 (2003) - [c5]Bo Yuan, Marcus Gallagher:
Playing in continuous spaces: some analysis and extension of population-based incremental learning. IEEE Congress on Evolutionary Computation 2003: 443-450 - [c4]Bo Yuan, Marcus Gallagher:
On building a principled framework for evaluating and testing evolutionary algorithms: a continuous landscape generator. IEEE Congress on Evolutionary Computation 2003: 451-458 - [c3]Marcus Gallagher, A. Ryan:
Learning to play Pac-Man: an evolutionary, rule-based approach. IEEE Congress on Evolutionary Computation 2003: 2462-2469 - 2002
- [j1]Marcus Gallagher, Tom Downs, Ian A. Wood:
Empirical Evidence for Ultrametric Structure in Multi layer Perceptron Error Surfaces. Neural Process. Lett. 16(2): 177-186 (2002) - 2001
- [c2]Marcus Gallagher:
Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem. ECML 2001: 157-166 - 2000
- [b1]Marcus Gallagher:
Multi-layer perceptron error surfaces: visualization, structure and modelling. University of Queensland, Australia, 2000
1990 – 1999
- 1999
- [c1]Marcus Gallagher, Marcus R. Frean, Tom Downs:
Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator. GECCO 1999: 840-846
Coauthor Index
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