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Journal of Computer Science and Technology ›› 2019, Vol. 34 ›› Issue (6): 1241-1257.doi: 10.1007/s11390-019-1973-1
• Artificial Intelligence and Pattern Recognition • Previous Articles Next Articles
Momodou L. Sanyang1,2, Ata Kabán1, Member, IEEE
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Technical Report, Utrecht University, 1999. https://homepages.cwi.nl/~bosman/publications/1999analgorithmicframework.pdf, June 2019. [11] Armañanzas R, Inza I, Santana R et al. A review of estimation of distribution algorithms in bioinformatics. BioData Mining, 2008, 1:Article No. 6. [12] Weicker K, Weicker N. On the improvement of coevolutionary optimizers by learning variable interdependencies. In Proc. the 1999 Congress on Evolutionary Computation, July 1999, pp.1627-1632. [13] Dong W, Chen T, Tiňo P, Yao X. Scaling up estimation of distribution algorithm for continuous optimisation. IEEE Transaction of Evolutionary Computation, 2013, 17(6):797-822. [14] Yang Z, Tang K, Yao X. Multilevel cooperative convolution for large scale optimization. In Proc. IEEE World Congress on Computational Intelligence, June 2008, pp.1663-1670. [15] Molina D, Lozano M, Sánchez A M, Herrera F. Memetic algorithms based on local search chains for large scale continuous optimisation problems:MA-SSW-Chains. Soft Computing, 2011, 15(11):2201-2220. [16] Shin S Y, Cho D Y, Zhang B T. Function optimization with latent variable models. In Proc. the 3rd International Symposium on Adaptive Systems, March 2001, pp.145-152. [17] Sanyang M L, Kabán A. REMEDA:Random embedding EDA for optimising functions with intrinsic dimension. In Proc. the 14th International Conference on Parallel Problem Solving from Nature, September 2016, pp.859-868. [18] Sanyang M L, Kabán A. Heavy tails with parameter adaptation in random projection based continuous EDA. In Proc. the 2015 IEEE Congress on Evolutionary Computation, May 2015, pp.2074-2081. [19] Yao X, Liu Y, Lin G. Evolutionary programming made faster. IEEE Transaction on Evolutionary Computation, 1999, 3(2):82-102. [20] Gao B, Wood I. TAM-EDA:Multivariate t distribution, archive and mutation based estimation of distribution algorithm. ANZIAM Journal, 2014, 54:720-746. [21] Gao B. Estimation of distribution algorithms for singleand multi-objective optimization[Ph.D. Thesis]. School of Mathematics and Physics, The University of Queensland, 2014. [22] Sanyang M L, Durrant R J, Kabán A. How effective is Cauchy-EDA in high dimensions? In Proc. the 2016 IEEE Congress on Evolutionary Computation, July 2016, pp.3409-3416. [23] Dang D C, Lehre P K, Nguyen P T H. Level-based analysis of the univariate marginal distribution algorithm. Algorithmica, 2018, 81(2):668-702. [24] Kabán A. On compressive ensemble induced regularisation:How close is the finite ensemble precision matrix to the infinite ensemble? In Proc. the 2017 International Conference on Algorithmic Learning Theory, October 2017, pp.617-628. [25] Kabán A. New bounds for compressive linear least squares regression. In Proc. the 17th International Conference on Artificial Intelligence and Statistics, April 2014, pp.448-456. [26] Achlioptas D. Database-friendly random projections:Johnson-Lindenstrauss with binary coins. Journal of Computer and System Sciences, 2003, 66(4):671-687. [27] Grahl J, Bosman P A, Rothlauf F. The correlation-triggered adaptive variance scaling IDEA. In Proc. the 2006 Genetic and Evolutionary Computation Conference, July 2006, pp.397-404. [28] Eiben A E, Hinterding R, Michalewicz Z. Parameter control in evolutionary algorithms. IEEE Transaction on Evolutionary Computation, 1999, 3(2):124-141. [29] Wong Y Y, Lee K H, Leung K S, Ho C W. A novel approach in parameter adaptation and diversity maintenance for genetic algorithms. Soft Computing, 2003, 7(8):506-515. [30] Beyer H G, Schwefel H P. Evolution strategies-A comprehensive introduction. Natural Computing, 1999, 1(1):3-52. [31] Tang K, Li X D, Suganthan P N, Yang Z, Weise T. Benchmark functions for the CEC'2010 special session and competition on large scale global optimization. Technical report, Nature Inspired Computation and Applications Laboratory, 2012. http://www.tflsgo.org/assets/cec2018/cec2-013-lsgo-benchmark-tech-report.pdf, June 2019. [32] Abramowitz M, Stegun I A, Morse P M (eds.). Handbook of Mathematical Functions with Formulas, Graphs and Mathematical Tables. National Bureau of Standards, 1964. |
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[2] | Nan Ding, Shu-De Zhou, and Zeng-Qi Sun. Histogram-Based Estimation of Distribution Algorithm: A Competent Method for Continuous Optimization [J]. , 2008, 23(1): 35-43 . |
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