| 2025 | FOGA | A Standardized Benchmark Set of Clustering Problem Instances for Comparing Black-Box Optimizers. | Diederick Vermetten, Catalin-Viorel Dinu, Marcus Gallagher |
| 2024 | GECCO | Towards an Improved Understanding of Features for More Interpretable Landscape Analysis. | Marcus Gallagher, Mario A. Muoz |
| 2024 | GECCO | Searching for Benchmark Problem Instances from Data-Driven Optimisation. | Sara Hajari, Marcus Gallagher |
| 2024 | GECCO | Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function. | Yukai Qiao, Marcus Gallagher |
| 2023 | GECCO | Modularity Based Linkage Model For Neuroevolution. | Yukai Qiao, Marcus Gallagher |
| 2023 | IJCNN | Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning. | Humphrey Munn, Marcus Gallagher |
| 2022 | GECCO | Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. | Jordan T. Bishop, Marcus Gallagher, Will N. Browne |
| 2022 | NOMS | E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. | Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann |
| 2021 | AAAI | Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. | Russell Tsuchida, Tim Pearce, Christopher van der Heide, Fred Roosta, Marcus Gallagher |
| 2021 | GECCO | A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. | Jordan T. Bishop, Marcus Gallagher, Will N. Browne |
| 2020 | PPSN | Optimality-Based Analysis of XCSF Compaction in Discrete Reinforcement Learning. | Jordan T. Bishop, Marcus Gallagher |
| 2020 | PPSN | Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces. | Nathaniel du Preez-Wilkinson, Marcus Gallagher |
| 2019 | AISTATS | Reversible Jump Probabilistic Programming. | David A. Roberts, Marcus Gallagher, Thomas Taimre |
| 2019 | CEC | Fitness Landscape Analysis in Data-Driven Optimization: An Investigation of Clustering Problems. | Marcus Gallagher |
| 2019 | GECCO | Exploring the MLDA benchmark on the nevergrad platform. | Jrmy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud |
| 2019 | IJCAI | Exchangeability and Kernel Invariance in Trained MLPs. | Russell Tsuchida, Fred (Farbod) Roosta, Marcus Gallagher |
| 2018 | ICML | Invariance of Weight Distributions in Rectified MLPs. | Russell Tsuchida, Farbod Roosta-Khorasani, Marcus Gallagher |
| 2018 | PPSN | Workshops at PPSN 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 Wrbel, Ales Zamuda |
| 2018 | PPSN | A Model-Based Framework for Black-Box Problem Comparison Using Gaussian Processes. | Sobia Saleem, Marcus Gallagher, Ian A. Wood |
| 2012 | CEC | Variable screening for reduced dependency modelling in Gaussian-based continuous Estimation of Distribution Algorithms. | Krishna Manjari Mishra, Marcus Gallagher |
| 2012 | PPSN | Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing. | Marcus Gallagher |
| 2012 | PPSN | Length Scale for Characterising Continuous Optimization Problems. | Rachael Morgan, Marcus Gallagher |
| 2011 | PAKDD | Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series. | Wei Luo, Marcus Gallagher |
| 2010 | ICDM | Unsupervised DRG Upcoding Detection in Healthcare Databases. | Wei Luo, Marcus Gallagher |
| 2010 | PPSN | When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure. | Rachael Morgan, Marcus Gallagher |
| 2009 | GECCO | Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. | Marcus Gallagher |
| 2009 | GECCO | Convergence analysis of UMDA | Bo Yuan, Marcus Gallagher |
| 2009 | GECCO | An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. | Bo Yuan, Marcus Gallagher |
| 2008 | IJCNN | An empirical study of the sample size variability of optimal active learning using Gaussian process regression. | Flora Yu-Hui Yeh, Marcus Gallagher |
| 2007 | CEC | Bayesian inference in estimation of distribution algorithms. | Marcus Gallagher, Ian A. Wood, Jonathan M. Keith, George Y. Sofronov |
| 2007 | CIBCB | A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. | Stefan Maetschke, Marcus Gallagher, Mikael Bodn |
| 2007 | ICECCS | An agent based approach to examining shared situation awareness. | Simon Connelly, Peter A. Lindsay, Marcus Gallagher |
| 2006 | CEC | A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. | Bo Yuan, Marcus Gallagher |
| 2005 | CEC | A hybrid approach to parameter tuning in genetic algorithms. | Bo Yuan, Marcus Gallagher |
| 2005 | CEC | Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA. | Bo Yuan, Marcus Gallagher |
| 2005 | GECCO | On the importance of diversity maintenance in estimation of distribution algorithms. | Bo Yuan, Marcus Gallagher |
| 2005 | GECCO | MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. | Bo Yuan, Marcus Gallagher, Stuart Crozier |
| 2005 | IDEAL | An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification. | Flora Yu-Hui Yeh, Marcus Gallagher |
| 2004 | IDEAL | Machine Learning for Matching Astronomy Catalogues. | David Rohde, Michael Drinkwater, Marcus Gallagher, Tom Downs, Marianne Doyle |
| 2004 | PPSN | Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. | Bo Yuan, Marcus Gallagher |
| 2003 | CEC | Learning to play Pac-Man: an evolutionary, rule-based approach. | Marcus Gallagher, A. Ryan |
| 2003 | CEC | Playing in continuous spaces: some analysis and extension of population-based incremental learning. | Bo Yuan, Marcus Gallagher |
| 2003 | CEC | On building a principled framework for evaluating and testing evolutionary algorithms: a continuous landscape generator. | Bo Yuan, Marcus Gallagher |
| 1999 | GECCO | Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator. | Marcus Gallagher, Marcus R. Frean, Tom Downs |