Marcus Gallagher
Orcid: 0000-0002-6694-9572Affiliations:
- University of Queensland, School of Information Technology and Electrical Engineering, St. Lucia, QLD, Australia
According to our database1,
Marcus Gallagher
authored at least 96 papers
between 1999 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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on zbmath.org
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on scopus.com
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on orcid.org
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Bibliography
2024
Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets.
J. Inf. Secur. Appl., February, 2024
2023
IEEE Trans. Games, March, 2023
Int. J. Inf. Sec., 2023
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
2022
An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability.
ACM Trans. Interact. Intell. Syst., 2022
Using regression models for characterizing and comparing black box optimization problems.
Swarm Evol. Comput., 2022
CoRR, 2022
Proceedings of the 2022 IEEE/IFIP Network Operations and Management Symposium, 2022
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the IEEE Conference on Dependable and Secure Computing, 2022
Examining Average and Discounted Reward Optimality Criteria in Reinforcement Learning.
Proceedings of the AI 2022: Advances in Artificial Intelligence, 2022
2021
CoRR, 2021
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
IEEE J. Biomed. Health Informatics, 2020
Considerations for selecting a machine learning technique for predicting deforestation.
Environ. Model. Softw., 2020
Average-reward model-free reinforcement learning: a systematic review and literature mapping.
CoRR, 2020
Fitness Landscape Features and Reward Shaping in Reinforcement Learning Policy Spaces.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020
An Implementation and Experimental Evaluation of a Modularity Explicit Encoding Method for Neuroevolution on Complex Learning Tasks.
Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020
2019
Inf. Sci., 2019
Evol. Comput., 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019
Fitness Landscape Analysis in Data-Driven Optimization: An Investigation of Clustering Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
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., 2018
Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018
Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Flood-Fill Q-Learning Updates for Learning Redundant Policies in Order to Interact with a Computer Screen by Clicking.
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018
2017
Soft Comput., 2017
Use of freely available datasets and machine learning methods in predicting deforestation.
Environ. Model. Softw., 2017
Parallel evolutionary algorithm for single and multi-objective optimisation: Differential evolution and constraints handling.
Appl. Soft Comput., 2017
Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution.
Proceedings of the Artificial Life and Computational Intelligence, 2017
2016
Towards improved benchmarking of black-box optimization algorithms using clustering problems.
Soft Comput., 2016
2015
Proceedings of the Artificial Life and Computational Intelligence, 2015
2014
Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements.
IEEE Trans. Evol. Comput., 2014
BMC Bioinform., 2014
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014
A Modified Screening Estimation of Distribution Algorithm for Large-Scale Continuous Optimization.
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014
2013
Proceedings of the 2013 IEEE Conference on Computational Inteligence in Games (CIG), 2013
2012
Using Landscape Topology to Compare Continuous Metaheuristics: A Framework and Case Study on EDAs and Ridge Structure.
Evol. Comput., 2012
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012
Beware the Parameters: Estimation of Distribution Algorithms Applied to Circles in a Square Packing.
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012
Variable screening for reduced dependency modelling in Gaussian-based continuous Estimation of Distribution Algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012
Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012
2011
IEEE Trans. Comput. Intell. AI Games, 2011
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011
2010
Using Gaussian Process with Test Rejection to Detect T-Cell Epitopes in Pathogen Genomes.
IEEE ACM Trans. Comput. Biol. Bioinform., 2010
When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure.
Proceedings of the Parallel Problem Solving from Nature, 2010
Proceedings of the ICDMW 2010, 2010
2009
An improved small-sample statistical test for comparing the success rates of evolutionary algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009
Convergence analysis of UMDA<sub>C</sub> with finite populations: a case study on flat landscapes.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009
Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noisy function testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009
Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009
2008
An empirical study of the sample size variability of optimal active learning using Gaussian process regression.
Proceedings of the International Joint Conference on Neural Networks, 2008
Proceedings of the 2008 IEEE Symposium on Computational Intelligence and Games, 2008
Proceedings of the 2008 IEEE Symposium on Computational Intelligence and Games, 2008
Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, 2008
2007
Proceedings of the Parameter Setting in Evolutionary Algorithms, 2007
Proceedings of the 12th International Conference on Engineering of Complex Computer Systems (ICECCS 2007), 2007
Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Games, 2007
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins.
Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007
Proceedings of the IEEE Congress on Evolutionary Computation, 2007
2006
A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA.
Proceedings of the Theory of Evolutionary Algorithms, 05.02. - 10.02.2006, 2006
2005
Evol. Comput., 2005
An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2005
MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005
Proceedings of the Genetic and Evolutionary Computation Conference, 2005
Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA.
Proceedings of the IEEE Congress on Evolutionary Computation, 2005
Proceedings of the IEEE Congress on Evolutionary Computation, 2005
2004
Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms.
Proceedings of the Parallel Problem Solving from Nature, 2004
Proceedings of the Intelligent Data Engineering and Automated Learning, 2004
2003
Visualization of learning in multilayer perceptron networks using principal component analysis.
IEEE Trans. Syst. Man Cybern. Part B, 2003
On building a principled framework for evaluating and testing evolutionary algorithms: a continuous landscape generator.
Proceedings of the IEEE Congress on Evolutionary Computation, 2003
Playing in continuous spaces: some analysis and extension of population-based incremental learning.
Proceedings of the IEEE Congress on Evolutionary Computation, 2003
Proceedings of the IEEE Congress on Evolutionary Computation, 2003
2002
Empirical Evidence for Ultrametric Structure in Multi layer Perceptron Error Surfaces.
Neural Process. Lett., 2002
2001
Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem.
Proceedings of the Machine Learning: EMCL 2001, 2001
2000
PhD thesis, 2000
1999
Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator.
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), 1999