Marcus Gallagher

124 papers A* 3A 9B 13C 4Misc 1Journal 55Unranked 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Robots. CoRR Humphrey Munn, Brendan Tidd, Peter Böhm, Marcus Gallagher, Gerard David Howard
2026	J	`jnl`	SimTO: A simulation-based topology optimization framework for bespoke soft robotic grippers. CoRR Kurt Enkera, Josh Pinskier, Marcus Gallagher, David Howard
2025	A	`conf`	A Standardized Benchmark Set of Clustering Problem Instances for Comparing Black-Box Optimizers. FOGA Diederick Vermetten, Catalin-Viorel Dinu, Marcus Gallagher
2025	J	`jnl`	A Standardized Benchmark Set of Clustering Problem Instances for Comparing Black-Box Optimizers. CoRR Diederick Vermetten, Catalin-Viorel Dinu, Marcus Gallagher
2025	J	`jnl`	AlgOS: Algorithm Operating System. CoRR Llewyn Salt, Marcus Gallagher
2025	J	`jnl`	An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems. Eng. Appl. Artif. Intell. Liam Daly Manocchio, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2025	J	`jnl`	Hyperparameter Optimisation with Practical Interpretability and Explanation Methods in Probabilistic Curriculum Learning. CoRR Llewyn Salt, Marcus Gallagher
2025	J	`jnl`	Probabilistic Curriculum Learning for Goal-Based Reinforcement Learning. CoRR Llewyn Salt, Marcus Gallagher
2025	J	`jnl`	Scalable Multi-Objective Robot Reinforcement Learning through Gradient Conflict Resolution. CoRR Humphrey Munn, Brendan Tidd, Peter Böhm, Marcus Gallagher, David Howard
2025	—	`conf`	Using Individual Problem Instances for Exploratory Black Box Optimisation Benchmarking: A Case Study Using XOR Neural Networks. AI (2) Marcus Gallagher
2024	—	`conf`	Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. GECCO Companion Yukai Qiao, Marcus Gallagher
2024	J	`jnl`	Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. CoRR Yukai Qiao, Marcus Gallagher
2024	J	`jnl`	Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets. J. Inf. Secur. Appl. Siamak Layeghy, Marcus Gallagher, Marius Portmann
2024	J	`jnl`	Feature extraction for machine learning-based intrusion detection in IoT networks. Digit. Commun. Networks Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann
2024	—	`conf`	Searching for Benchmark Problem Instances from Data-Driven Optimisation. GECCO Companion Sara Hajari, Marcus Gallagher
2024	—	`conf`	Towards an Improved Understanding of Features for More Interpretable Landscape Analysis. GECCO Companion Marcus Gallagher, Mario A. Muñoz
2024	J	`jnl`	Whole-Body Dynamic Throwing with Legged Manipulators. CoRR Humphrey Munn, Brendan Tidd, David Howard, Marcus Gallagher
2023	J	`jnl`	A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning Policies. CoRR Jordan T. Bishop, Marcus Gallagher, Will N. Browne
2023	J	`jnl`	From zero-shot machine learning to zero-day attack detection. Int. J. Inf. Sec. Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2023	J	`jnl`	Guest Editorial: Special Issue on Evolutionary Computation for Games. IEEE Trans. Games Jacob Schrum, Jialin Liu, Cameron Browne, Anikó Ekárt, Marcus Gallagher
2023	—	`conf`	Modularity Based Linkage Model For Neuroevolution. GECCO Companion Yukai Qiao, Marcus Gallagher
2023	J	`jnl`	Modularity based linkage model for neuroevolution. CoRR Yukai Qiao, Marcus Gallagher
2023	J	`jnl`	Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCS. CoRR Jordan T. Bishop, Marcus Gallagher, Will N. Browne
2023	B	`conf`	Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. IJCNN Humphrey Munn, Marcus Gallagher
2022	J	`jnl`	An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability. ACM Trans. Interact. Intell. Syst. Sabrina B. Caldwell, Penny Sweetser, Nicholas O'Donnell, Matthew James Knight, Matthew Aitchison, Tom Gedeon, Daniel Johnson, Margot Brereton, Marcus Gallagher, David Conroy
2022	J	`jnl`	Approximate discounting-free policy evaluation from transient and recurrent states. CoRR Vektor Dewanto, Marcus Gallagher
2022	B	`conf`	E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. NOMS Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	Misc	`conf`	Examining Average and Discounted Reward Optimality Criteria in Reinforcement Learning. AI Vektor Dewanto, Marcus Gallagher
2022	—	`conf`	Graph Neural Network-based Android Malware Classification with Jumping Knowledge. DSC Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	J	`jnl`	Graph Neural Network-based Android Malware Classification with Jumping Knowledge. CoRR Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	J	`jnl`	Modularity in NEAT Reinforcement Learning Networks. CoRR Humphrey Munn, Marcus Gallagher
2022	A	`conf`	Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. GECCO Jordan T. Bishop, Marcus Gallagher, Will N. Browne
2022	J	`jnl`	Using regression models for characterizing and comparing black box optimization problems. Swarm Evol. Comput. Sobia Saleem, Marcus Gallagher
2021	—	`conf`	A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. GECCO Companion Jordan T. Bishop, Marcus Gallagher, Will N. Browne
2021	J	`jnl`	A nearly Blackwell-optimal policy gradient method. CoRR Vektor Dewanto, Marcus Gallagher
2021	A*	`conf`	Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. AAAI Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher
2021	J	`jnl`	Benchmarking the Benchmark - Analysis of Synthetic NIDS Datasets. CoRR Siamak Layeghy, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. CoRR Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	Examining average and discounted reward optimality criteria in reinforcement learning. CoRR Vektor Dewanto, Marcus Gallagher
2021	J	`jnl`	Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks. CoRR Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	From Zero-Shot Machine Learning to Zero-Day Attack Detection. CoRR Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2020	—	`conf`	A Novel Mutation Operator for Variable Length Algorithms. Australasian Conference on Artificial Intelligence Saskia Van Ryt, Marcus Gallagher, Ian A. Wood
2020	—	`ed.`	AI 2020: Advances in Artificial Intelligence - 33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29-30, 2020, Proceedings Australasian Conference on Artificial Intelligence Marcus Gallagher, Nour Moustafa, Erandi Lakshika
2020	—	`conf`	An Implementation and Experimental Evaluation of a Modularity Explicit Encoding Method for Neuroevolution on Complex Learning Tasks. Australasian Conference on Artificial Intelligence Yukai Qiao, Marcus Gallagher
2020	J	`jnl`	Average-reward model-free reinforcement learning: a systematic review and literature mapping. CoRR Vektor Dewanto, George Dunn, Ali Eshragh, Marcus Gallagher, Fred Roosta
2020	J	`jnl`	Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. CoRR Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher
2020	J	`jnl`	Considerations for selecting a machine learning technique for predicting deforestation. Environ. Model. Softw. Helen Mayfield, Carl S. Smith, Marcus Gallagher, Marc Hockings
2020	—	`conf`	Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces. PPSN (2) Nathaniel du Preez-Wilkinson, Marcus Gallagher
2020	J	`jnl`	Network Analysis and Visualisation of Opioid Prescribing Data. IEEE J. Biomed. Health Informatics Xuelei Hu, Marcus Gallagher, William Loveday, Abhilash Dev, Jason P. Connor
2020	—	`conf`	Optimality-Based Analysis of XCSF Compaction in Discrete Reinforcement Learning. PPSN (2) Jordan T. Bishop, Marcus Gallagher
2020	J	`jnl`	Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning. CoRR Jordan T. Bishop, Marcus Gallagher
2019	J	`jnl`	Direct Feature Evaluation in Black-Box Optimization Using Problem Transformations. Evol. Comput. Sobia Saleem, Marcus Gallagher, Ian A. Wood
2019	A*	`conf`	Exchangeability and Kernel Invariance in Trained MLPs. IJCAI Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher
2019	—	`conf`	Exploring the MLDA benchmark on the nevergrad platform. GECCO (Companion) Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud
2019	B	`conf`	Fitness Landscape Analysis in Data-Driven Optimization: An Investigation of Clustering Problems. CEC Marcus Gallagher
2019	J	`jnl`	Quantitative measure of nonconvexity for black-box continuous functions. Inf. Sci. Kenichi Tamura, Marcus Gallagher
2019	A	`conf`	Reversible Jump Probabilistic Programming. AISTATS David A. Roberts, Marcus Gallagher, Thomas Taimre
2019	J	`jnl`	Richer priors for infinitely wide multi-layer perceptrons. CoRR Russell Tsuchida, Fred Roosta, Marcus Gallagher
2018	—	`conf`	A Model-Based Framework for Black-Box Problem Comparison Using Gaussian Processes. PPSN (2) Sobia Saleem, Marcus Gallagher, Ian A. Wood
2018	J	`jnl`	Exchangeability and Kernel Invariance in Trained MLPs. CoRR Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher
2018	—	`conf`	Flood-Fill Q-Learning Updates for Learning Redundant Policies in Order to Interact with a Computer Screen by Clicking. Australasian Conference on Artificial Intelligence Nathaniel du Preez-Wilkinson, Marcus Gallagher, Xuelei Hu
2018	—	`conf`	Intra-task Curriculum Learning for Faster Reinforcement Learning in Video Games. Australasian Conference on Artificial Intelligence Nathaniel du Preez-Wilkinson, Marcus Gallagher, Xuelei Hu
2018	A*	`conf`	Invariance of Weight Distributions in Rectified MLPs. ICML Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher
2018	J	`jnl`	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. Peter A. N. Bosman, Marcus Gallagher
2018	—	`conf`	Workshops at PPSN 2018. PPSN (2) 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
2017	J	`jnl`	Analysing and characterising optimization problems using length scale. Soft Comput. Rachael Morgan, Marcus Gallagher
2017	—	`conf`	Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution. ACALCI Sobia Saleem, Marcus Gallagher
2017	J	`jnl`	Invariance of Weight Distributions in Rectified MLPs. CoRR Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher
2017	J	`jnl`	Parallel evolutionary algorithm for single and multi-objective optimisation: Differential evolution and constraints handling. Appl. Soft Comput. Dorival M. Pedroso, Mohammad Reza Bonyadi, Marcus Gallagher
2017	J	`jnl`	Use of freely available datasets and machine learning methods in predicting deforestation. Environ. Model. Softw. Helen Mayfield, Carl S. Smith, Marcus Gallagher, Marc Hockings
2016	J	`jnl`	Towards improved benchmarking of black-box optimization algorithms using clustering problems. Soft Comput. Marcus Gallagher
2015	J	`jnl`	A Stochastic Process Model of Classical Search. CoRR Dimitri Klimenko, Hanna Kurniawati, Marcus Gallagher
2015	—	`conf`	Detecting Anomalies in Controlled Drug Prescription Data Using Probabilistic Models. ACALCI Xuelei Hu, Marcus Gallagher, William Loveday, Jason P. Connor, Janet Wiles
2014	—	`conf`	A Modified Screening Estimation of Distribution Algorithm for Large-Scale Continuous Optimization. SEAL Krishna Manjari Mishra, Marcus Gallagher
2014	—	`conf`	Clustering Problems for More Useful Benchmarking of Optimization Algorithms. SEAL Marcus Gallagher
2014	J	`jnl`	Detecting contaminated birthdates using generalized additive models. BMC Bioinform. Wei Luo, Marcus Gallagher, Bill Loveday, Susan Ballantyne, Jason P. Connor, Janet Wiles
2014	—	`conf`	Fitness Landscape Analysis of Circles in a Square Packing Problems. SEAL Rachael Morgan, Marcus Gallagher
2014	J	`jnl`	Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements. IEEE Trans. Evol. Comput. Rachael Morgan, Marcus Gallagher
2013	J	`jnl`	Parameter-Free Search of Time-Series Discord. J. Comput. Sci. Technol. Wei Luo, Marcus Gallagher, Janet Wiles
2013	—	`conf`	The turing test track of the 2012 Mario AI Championship: Entries and evaluation. CIG 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
2012	—	`conf`	Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing. PPSN (2) Marcus Gallagher
2012	—	`conf`	Game Designers Training First Person Shooter Bots. Australasian Conference on Artificial Intelligence Michelle McPartland, Marcus Gallagher
2012	—	`conf`	Interactively training first person shooter bots. CIG Michelle McPartland, Marcus Gallagher
2012	J	`jnl`	Introducing Cloud Computing Topics in Curricula. J. Inf. Syst. Educ. Ling Chen, Yang Liu, Marcus Gallagher, Bernard Pailthorpe, Shazia Sadiq, Heng Tao Shen, Xue Li
2012	—	`conf`	Length Scale for Characterising Continuous Optimization Problems. PPSN (1) Rachael Morgan, Marcus Gallagher
2012	J	`jnl`	Using Landscape Topology to Compare Continuous Metaheuristics: A Framework and Case Study on EDAs and Ridge Structure. Evol. Comput. R. Morgan, Marcus Gallagher
2012	B	`conf`	Variable screening for reduced dependency modelling in Gaussian-based continuous Estimation of Distribution Algorithms. IEEE Congress on Evolutionary Computation Krishna Manjari Mishra, Marcus Gallagher
2011	—	`conf`	Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series. PAKDD (2) Wei Luo, Marcus Gallagher
2011	J	`jnl`	Reinforcement Learning in First Person Shooter Games. IEEE Trans. Comput. Intell. AI Games Michelle McPartland, Marcus Gallagher
2010	—	`conf`	Unsupervised DRG Upcoding Detection in Healthcare Databases. ICDM Workshops Wei Luo, Marcus Gallagher
2010	J	`jnl`	Using Gaussian Process with Test Rejection to Detect T-Cell Epitopes in Pathogen Genomes. IEEE ACM Trans. Comput. Biol. Bioinform. Liwen You, Vladimir Brusic, Marcus Gallagher, Mikael Bodén
2010	—	`conf`	When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure. PPSN (1) Rachael Morgan, Marcus Gallagher
2009	A	`conf`	An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. GECCO Bo Yuan, Marcus Gallagher
2009	—	`conf`	Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. GECCO (Companion) Marcus Gallagher
2009	A	`conf`	Convergence analysis of UMDA GECCO Bo Yuan, Marcus Gallagher
2008	B	`conf`	An empirical study of the sample size variability of optimal active learning using Gaussian process regression. IJCNN Flora Yu-Hui Yeh, Marcus Gallagher
2008	—	`conf`	An influence map model for playing Ms. Pac-Man. CIG Nathan Wirth, Marcus Gallagher
2008	—	`conf`	Creating a multi-purpose first person shooter bot with reinforcement learning. CIG Michelle McPartland, Marcus Gallagher
2008	—	`conf`	Learning to be a Bot: Reinforcement Learning in Shooter Games. AIIDE Michelle McPartland, Marcus Gallagher
2007	C	`conf`	A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. CIBCB Stefan Maetschke, Marcus Gallagher, Mikael Bodén
2007	B	`conf`	An agent based approach to examining shared situation awareness. ICECCS Simon Connelly, Peter A. Lindsay, Marcus Gallagher
2007	B	`conf`	Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation Marcus Gallagher, Ian A. Wood, Jonathan M. Keith, George Y. Sofronov
2007	—	`ch.`	Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks. Parameter Setting in Evolutionary Algorithms Bo Yuan, Marcus Gallagher
2007	—	`conf`	Evolving Pac-Man Players: Can We Learn from Raw Input? CIG Marcus Gallagher, Mark Ledwich
2006	B	`conf`	A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. IEEE Congress on Evolutionary Computation Bo Yuan, Marcus Gallagher
2006	—	`conf`	A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. Theory of Evolutionary Algorithms Marcus Gallagher, Bo Yuan
2006	J	`jnl`	A general-purpose tunable landscape generator. IEEE Trans. Evol. Comput. Marcus Gallagher, Bo Yuan
2005	B	`conf`	A hybrid approach to parameter tuning in genetic algorithms. Congress on Evolutionary Computation Bo Yuan, Marcus Gallagher
2005	C	`conf`	An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification. IDEAL Flora Yu-Hui Yeh, Marcus Gallagher
2005	B	`conf`	Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA. Congress on Evolutionary Computation Bo Yuan, Marcus Gallagher
2005	C	`ed.`	Intelligent Data Engineering and Automated Learning - IDEAL 2005, 6th International Conference, Brisbane, Australia, July 6-8, 2005, Proceedings IDEAL Marcus Gallagher, James M. Hogan, Frédéric Maire
2005	A	`conf`	MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. GECCO Bo Yuan, Marcus Gallagher, Stuart Crozier
2005	A	`conf`	On the importance of diversity maintenance in estimation of distribution algorithms. GECCO Bo Yuan, Marcus Gallagher
2005	J	`jnl`	Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. Evol. Comput. Marcus Gallagher, Marcus R. Frean
2004	C	`conf`	Machine Learning for Matching Astronomy Catalogues. IDEAL David Rohde, Michael Drinkwater, Marcus Gallagher, Tom Downs, Marianne Doyle
2004	A	`conf`	Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. PPSN Bo Yuan, Marcus Gallagher
2003	B	`conf`	Learning to play Pac-Man: an evolutionary, rule-based approach. IEEE Congress on Evolutionary Computation Marcus Gallagher, A. Ryan
2003	B	`conf`	On building a principled framework for evaluating and testing evolutionary algorithms: a continuous landscape generator. IEEE Congress on Evolutionary Computation Bo Yuan, Marcus Gallagher
2003	B	`conf`	Playing in continuous spaces: some analysis and extension of population-based incremental learning. IEEE Congress on Evolutionary Computation Bo Yuan, Marcus Gallagher
2003	J	`jnl`	Visualization of learning in multilayer perceptron networks using principal component analysis. IEEE Trans. Syst. Man Cybern. Part B Marcus Gallagher, Tom Downs
2002	J	`jnl`	Empirical Evidence for Ultrametric Structure in Multi layer Perceptron Error Surfaces. Neural Process. Lett. Marcus Gallagher, Tom Downs, Ian A. Wood
2001	—	`conf`	Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem. ECML Marcus Gallagher
2000	—	`—`	Multi-layer perceptron error surfaces: visualization, structure and modelling Marcus Gallagher
1999	A	`conf`	Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator. GECCO Marcus Gallagher, Marcus R. Frean, Tom Downs