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Publications of Author

1. Marcus Gallagher
   Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem. [Citation Graph (0, 0)][DBLP]
   ECML, 2001, pp:157-166 [Conf]
   
2. Marcus Gallagher, Marcus R. Frean, Tom Downs
   Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator. [Citation Graph (0, 0)][DBLP]
   GECCO, 1999, pp:840-846 [Conf]
   
3. Bo Yuan, Marcus Gallagher
   On the importance of diversity maintenance in estimation of distribution algorithms. [Citation Graph (0, 0)][DBLP]
   GECCO, 2005, pp:719-726 [Conf]
   
4. Bo Yuan, Marcus Gallagher, Stuart Crozier
   MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. [Citation Graph (0, 0)][DBLP]
   GECCO, 2005, pp:2141-2148 [Conf]
   
5. David Rohde, Michael Drinkwater, Marcus Gallagher, Tom Downs, Marianne Doyle
   Machine Learning for Matching Astronomy Catalogues. [Citation Graph (0, 0)][DBLP]
   IDEAL, 2004, pp:702-707 [Conf]
   
6. Flora Yu-Hui Yeh, Marcus Gallagher
   An Empirical Study of Hoeffding Racing for Model Selection in k-Nearest Neighbor Classification. [Citation Graph (0, 0)][DBLP]
   IDEAL, 2005, pp:220-227 [Conf]
   
7. Bo Yuan, Marcus Gallagher
   Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. [Citation Graph (0, 0)][DBLP]
   PPSN, 2004, pp:172-181 [Conf]
   
8. Marcus Gallagher, Marcus R. Frean
   Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. [Citation Graph (0, 0)][DBLP]
   Evolutionary Computation, 2005, v:13, n:1, pp:29-42 [Journal]
   
9. Marcus Gallagher, Tom Downs, Ian Wood
   Empirical Evidence for Ultrametric Structure in Multi layer Perceptron Error Surfaces. [Citation Graph (0, 0)][DBLP]
   Neural Processing Letters, 2002, v:16, n:2, pp:177-186 [Journal]
   
10. Marcus Gallagher, Bo Yuan
    A general-purpose tunable landscape generator. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2006, v:10, n:5, pp:590-603 [Journal]
    
11. Marcus Gallagher, Tom Downs
    Visualization of learning in multilayer perceptron networks using principal component analysis. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2003, v:33, n:1, pp:28-34 [Journal]
    
12. Simon Connelly, Peter A. Lindsay, Marcus Gallagher
    An agent based approach to examining shared situation awareness. [Citation Graph (0, 0)][DBLP]
    ICECCS, 2007, pp:138-147 [Conf]
    
13. Bo Yuan, Marcus Gallagher
    A hybrid approach to parameter tuning in genetic algorithms. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:1096-1103 [Conf]
    
14. Bo Yuan, Marcus Gallagher
    Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:1792-1799 [Conf]
    
15. 
    A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. [Citation Graph (, )][DBLP]
    
    
16. 
    A Mathematical Modelling Technique for the Analysis of the Dynamics of a Simple Continuous EDA. [Citation Graph (, )][DBLP]
    
    
17. 
    An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. [Citation Graph (, )][DBLP]
    
    
18. 
    Convergence analysis of UMDA_C with finite populations: a case study on flat landscapes. [Citation Graph (, )][DBLP]
    
    
19. 
    Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. [Citation Graph (, )][DBLP]
    
    
20. 
    An empirical study of the sample size variability of optimal active learning using Gaussian process regression. [Citation Graph (, )][DBLP]
    
    
21. 
    When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure. [Citation Graph (, )][DBLP]
    
    
22. 
    Learning to be a Bot: Reinforcement Learning in Shooter Games. [Citation Graph (, )][DBLP]
    
    
23. 
    Playing in continuous spaces: some analysis and extension of population-based incremental learning. [Citation Graph (, )][DBLP]
    
    
24. 
    On building a principled framework for evaluating and testing evolutionary algorithms: a continuous landscape generator. [Citation Graph (, )][DBLP]
    
    
25. 
    Bayesian inference in estimation of distribution algorithms. [Citation Graph (, )][DBLP]