Marcus Gallagher

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 61

Top Venues

CoRR

GECCO Companion

Australasian Conference on Artificial Intelligence

PPSN (2)

Publications

Sara Hajari, Marcus Gallagher
Searching for Benchmark Problem Instances from Data-Driven Optimisation. GECCO Companion (2024)
Siamak Layeghy, Marcus Gallagher, Marius Portmann
Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets. J. Inf. Secur. Appl. 80 (2024)
Yukai Qiao, Marcus Gallagher
Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. GECCO Companion (2024)
Yukai Qiao, Marcus Gallagher
Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. CoRR (2024)
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) (2024)
Marcus Gallagher, Mario A. Muñoz
Towards an Improved Understanding of Features for More Interpretable Landscape Analysis. GECCO Companion (2024)
Jordan T. Bishop, Marcus Gallagher, Will N. Browne
A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning Policies. CoRR (2023)
Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
From zero-shot machine learning to zero-day attack detection. Int. J. Inf. Sec. 22 (4) (2023)
Humphrey Munn, Marcus Gallagher
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. IJCNN (2023)
Jacob Schrum, Jialin Liu, Cameron Browne, Anikó Ekárt, Marcus Gallagher
Guest Editorial: Special Issue on Evolutionary Computation for Games. IEEE Trans. Games 15 (1) (2023)
Yukai Qiao, Marcus Gallagher
Modularity based linkage model for neuroevolution. CoRR (2023)
Yukai Qiao, Marcus Gallagher
Modularity Based Linkage Model For Neuroevolution. GECCO Companion (2023)
Jordan T. Bishop, Marcus Gallagher, Will N. Browne
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCS. CoRR (2023)
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)
Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. DSC (2022)
Vektor Dewanto, Marcus Gallagher
Approximate discounting-free policy evaluation from transient and recurrent states. CoRR (2022)
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) (2022)
Humphrey Munn, Marcus Gallagher
Modularity in NEAT Reinforcement Learning Networks. CoRR (2022)
Vektor Dewanto, Marcus Gallagher
Examining Average and Discounted Reward Optimality Criteria in Reinforcement Learning. AI (2022)
Jordan T. Bishop, Marcus Gallagher, Will N. Browne
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. GECCO (2022)
Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. CoRR (2022)
Sobia Saleem, Marcus Gallagher
Using regression models for characterizing and comparing black box optimization problems. Swarm Evol. Comput. 68 (2022)
Siamak Layeghy, Marcus Gallagher, Marius Portmann
Benchmarking the Benchmark - Analysis of Synthetic NIDS Datasets. CoRR (2021)
Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks. CoRR (2021)
Vektor Dewanto, Marcus Gallagher
Examining average and discounted reward optimality criteria in reinforcement learning. CoRR (2021)
Jordan T. Bishop, Marcus Gallagher, Will N. Browne
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. GECCO Companion (2021)
Vektor Dewanto, Marcus Gallagher
A nearly Blackwell-optimal policy gradient method. CoRR (2021)
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)
Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. CoRR (2021)
Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
From Zero-Shot Machine Learning to Zero-Day Attack Detection. CoRR (2021)
Saskia Van Ryt, Marcus Gallagher, Ian Wood
A Novel Mutation Operator for Variable Length Algorithms. Australasian Conference on Artificial Intelligence (2020)
Jordan T. Bishop, Marcus Gallagher
Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning. CoRR (2020)
Vektor Dewanto, George Dunn, Ali Eshragh, Marcus Gallagher, Fred Roosta
Average-reward model-free reinforcement learning: a systematic review and literature mapping. CoRR (2020)
Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. CoRR (2020)
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)
Jordan T. Bishop, Marcus Gallagher
Optimality-Based Analysis of XCSF Compaction in Discrete Reinforcement Learning. PPSN (2) (2020)
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) (2020)
Helen Mayfield, Carl S. Smith, Marcus Gallagher, Marc Hockings
Considerations for selecting a machine learning technique for predicting deforestation. Environ. Model. Softw. 131 (2020)
Nathaniel du Preez-Wilkinson, Marcus Gallagher
Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces. PPSN (2) (2020)
Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud
Exploring the MLDA benchmark on the nevergrad platform. GECCO (Companion) (2019)
Sobia Saleem, Marcus Gallagher, Ian Wood
Direct Feature Evaluation in Black-Box Optimization Using Problem Transformations. Evol. Comput. 27 (1) (2019)
David A. Roberts, Marcus Gallagher, Thomas Taimre
Reversible Jump Probabilistic Programming. AISTATS (2019)
Russell Tsuchida, Fred Roosta, Marcus Gallagher
Richer priors for infinitely wide multi-layer perceptrons. CoRR (2019)
Marcus Gallagher
Fitness Landscape Analysis in Data-Driven Optimization: An Investigation of Clustering Problems. CEC (2019)
Kenichi Tamura, Marcus Gallagher
Quantitative measure of nonconvexity for black-box continuous functions. Inf. Sci. 476 (2019)
Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher
Exchangeability and Kernel Invariance in Trained MLPs. IJCAI (2019)
Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher
Invariance of Weight Distributions in Rectified MLPs. ICML (2018)
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)
Sobia Saleem, Marcus Gallagher, Ian Wood
A Model-Based Framework for Black-Box Problem Comparison Using Gaussian Processes. PPSN (2) (2018)
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) (2018)
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)
Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher
Exchangeability and Kernel Invariance in Trained MLPs. CoRR (2018)
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)
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 (2017)
Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher
Invariance of Weight Distributions in Rectified MLPs. CoRR (2017)
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 (2017)
Sobia Saleem, Marcus Gallagher
Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution. ACALCI (2017)
Rachael Morgan, Marcus Gallagher
Analysing and characterising optimization problems using length scale. Soft Comput. 21 (7) (2017)
Marcus Gallagher
Towards improved benchmarking of black-box optimization algorithms using clustering problems. Soft Comput. 20 (10) (2016)
Xuelei Hu, Marcus Gallagher, William Loveday, Jason P. Connor, Janet Wiles
Detecting Anomalies in Controlled Drug Prescription Data Using Probabilistic Models. ACALCI (2015)
Dimitri Klimenko, Hanna Kurniawati, Marcus Gallagher
A Stochastic Process Model of Classical Search. CoRR (2015)
Krishna Manjari Mishra, Marcus Gallagher
A Modified Screening Estimation of Distribution Algorithm for Large-Scale Continuous Optimization. SEAL (2014)
Wei Luo, Marcus Gallagher, Bill Loveday, Susan Ballantyne, Jason P. Connor, Janet Wiles
Detecting contaminated birthdates using generalized additive models. BMC Bioinform. 15 (2014)
Rachael Morgan, Marcus Gallagher
Fitness Landscape Analysis of Circles in a Square Packing Problems. SEAL (2014)
Rachael Morgan, Marcus Gallagher
Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements. IEEE Trans. Evol. Comput. 18 (3) (2014)
Marcus Gallagher
Clustering Problems for More Useful Benchmarking of Optimization Algorithms. SEAL (2014)
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)
Wei Luo, Marcus Gallagher, Janet Wiles
Parameter-Free Search of Time-Series Discord. J. Comput. Sci. Technol. 28 (2) (2013)
Michelle McPartland, Marcus Gallagher
Interactively training first person shooter bots. CIG (2012)
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) (2012)
Marcus Gallagher
Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing. PPSN (2) (2012)
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)
Rachael Morgan, Marcus Gallagher
Length Scale for Characterising Continuous Optimization Problems. PPSN (1) (2012)
Michelle McPartland, Marcus Gallagher
Game Designers Training First Person Shooter Bots. Australasian Conference on Artificial Intelligence (2012)
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) (2012)
Michelle McPartland, Marcus Gallagher
Reinforcement Learning in First Person Shooter Games. IEEE Trans. Comput. Intell. AI Games 3 (1) (2011)
Wei Luo, Marcus Gallagher
Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series. PAKDD (2) (2011)
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)
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) (2010)
Wei Luo, Marcus Gallagher
Unsupervised DRG Upcoding Detection in Healthcare Databases. ICDM Workshops (2010)
Bo Yuan, Marcus Gallagher
An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. GECCO (2009)
Marcus Gallagher
Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. GECCO (Companion) (2009)
Bo Yuan, Marcus Gallagher
with finite populations: a case study on flat landscapes. GECCO (2009)
Nathan Wirth, Marcus Gallagher
An influence map model for playing Ms. Pac-Man. CIG (2008)
Michelle McPartland, Marcus Gallagher
Learning to be a Bot: Reinforcement Learning in Shooter Games. AIIDE (2008)
Flora Yu-Hui Yeh, Marcus Gallagher
An empirical study of the sample size variability of optimal active learning using Gaussian process regression. IJCNN (2008)
Michelle McPartland, Marcus Gallagher
Creating a multi-purpose first person shooter bot with reinforcement learning. CIG (2008)
Stefan Maetschke, Marcus Gallagher, Mikael Bodén
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. CIBCB (2007)
Marcus Gallagher, Mark Ledwich
Evolving Pac-Man Players: Can We Learn from Raw Input? CIG (2007)
Marcus Gallagher, Ian Wood, Jonathan M. Keith, George Y. Sofronov
Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (2007)
Simon Connelly, Peter A. Lindsay, Marcus Gallagher
An agent based approach to examining shared situation awareness. ICECCS (2007)
Marcus Gallagher, Bo Yuan
A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. Theory of Evolutionary Algorithms (2006)
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)
Marcus Gallagher, Bo Yuan
A general-purpose tunable landscape generator. IEEE Trans. Evol. Comput. 10 (5) (2006)
Bo Yuan, Marcus Gallagher, Stuart Crozier
MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. GECCO (2005)
Marcus Gallagher, Marcus R. Frean
Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. Evol. Comput. 13 (1) (2005)
Bo Yuan, Marcus Gallagher
On the importance of diversity maintenance in estimation of distribution algorithms. GECCO (2005)
Bo Yuan, Marcus Gallagher
A hybrid approach to parameter tuning in genetic algorithms. Congress on Evolutionary Computation (2005)
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)
Flora Yu-Hui Yeh, Marcus Gallagher
An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification. IDEAL (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

Marcus Gallagher