15 resultados para Computer Science, theory and methods
em Aberystwyth University Repository - Reino Unido
Resumo:
Rowland, J. J. (2003) Generalisation and Model Selection in Supervised Learning with Evolutionary Computation. European Workshop on Evolutionary Computation in Bioinformatics: EvoBio 2003. Lecture Notes in Computer Science (Springer), Vol 2611, pp 119-130
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Murphy, L. and Thomas, L. 2008. Dangers of a fixed mindset: implications of self-theories research for computer science education. In Proceedings of the 13th Annual Conference on innovation and Technology in Computer Science Education (Madrid, Spain, June 30 - July 02, 2008). ITiCSE '08. ACM, New York, NY, 271-275.
Resumo:
Meng, Q., & Lee, M. (2005). Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics. Wermter, S., Palm, G., & Elshaw, M. (Eds.), In: Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience. (pp. 315-332). (Lecture Notes in Computer Science). Springer Berlin Heidelberg.
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Clare, A. (2005) Integration of genomic and phenotypic data. In Data Analysis and Visualization in Genomics and Proteomics, Eds. Francisco Azuaje and Joaquin Dopazo, Wiley, London. ISBN: 0-470-09439-7
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King, R. D. and Wise, P. H. and Clare, A. (2004) Confirmation of Data Mining Based Predictions of Protein Function. Bioinformatics 20(7), 1110-1118
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Clare, A. and King R.D. (2003) Data mining the yeast genome in a lazy functional language. In Practical Aspects of Declarative Languages (PADL'03) (won Best/Most Practical Paper award).
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King, R. D. and Ouali, M. (2004) Poly-transformation. In proceedings of 5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004). Springer LNCS 3177 p99-107
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Rowland, J. J. (2004) On Genetic Programming and Knowledge Discovery in Transcriptome Data. Proc. IEEE Congress on Evolutionary Computation, Portland, Oregon. pp 158-165. ISBN 0-7803-8515-2
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Rowland, J.J. (2003) Model Selection Methodology in Supervised Learning with Evolutionary Computation. BioSystems 72, 1-2, pp 187-196, Nov
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Janet Taylor, Ross D King, Thomas Altmann and Oliver Fiehn (2002). Application of metabolomics to plant genotype discrimination using statistics and machine learning. 1st European Conference on Computational Biology (ECCB). (published as a journal supplement in Bioinformatics 18: S241-S248).
Resumo:
Bradshaw, K. & Urquhart, C. (2005). Theory and practice in strategic planning for health information systems. In: D. Wainwright (Ed.), UK Academy for Information Systems 10th conference 2005, 22-24 March 2005 (CD-ROM). Newcastle upon Tyne: Northumbria University.
Resumo:
Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.
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Riley, M. C., Clare, A., King, R. D. (2007). Locational distribution of gene functional classes in Arabidopsis thaliana. BMC Bioinformatics 8, Article No: 112 Sponsorship: EPSRC / RAEng
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Scott, Len, and Peter Jackson, 'The Study of Intelligence in Theory and Practice', Intelligence and National Security, (2004) 19(2) pp.139-169 RAE2008
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Binding, David; Bell, D.; Walters, K., (2006) 'The Oscillatory Squeeze flow rheometer: Comprehensive theory and a new experimental facility', Rheologica Acta 46 pp.111-121 RAE2008