Items where School is "University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Machine learning in computational biology

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Number of items at this level: 89.

A

Aldehim, Ghadah, De La Iglesia, Beatriz and Wang, Wenjia (2014) Heuristic Ensemble of Filters for Reliable Feature Selection. In: International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014), 2014-05-10.

Aldehim, Ghadah and Wang, Wenjia (2015) Weighted Heuristic Ensemble of Filters. In: SAI Intelligent Systems Conference 2015, 2015-11-10 - 2015-11-11.

Alotaibi, K., Rayward-Smith, V.J., Wang, W. and De La Iglesia, B. (2012) Non-linear dimensionality reduction for privacy-preserving data classification. In: Proceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012. UNSPECIFIED, pp. 694-701. ISBN 9780769548487

Alqurashi, Tahani and Wang, Wenjia (2014) A Graph based Methodology for Web Structure Mining:with a Case Study on the Webs of UK Universities. In: International Conference on Web Intelligence, Mining and Semantics, 2014-06-02 - 2014-06-05.

Alqurashi, Tahani and Wang, Wenjia (2015) A New Consensus Function based on Dual-Similarity Measurements for Clustering Ensemble. In: IEEE DSAA’15 (International Conference on Data Science and Advanced Analytics);, 2015-10-19 - 2015-10-21.

Alshaqsi, Jamil and Wang, Wenjia (2013) UNSPECIFIED In: UNSPECIFIED IEEE Press. ISBN 978-1-4673-4651-1

B

Bagnall, AJ and Cawley, GC (2003) Learning classifier systems for data mining: a comparison of XCS with other classifiers for the Forest Cover data set. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

Bagnall, AJ, Cawley, GC, Bull, L, Whittley, IM, Studley, M, Pettipher, M and Tekiner, F (2007) Super Computer Heterogeneous Classifier Meta-Ensembles. International Journal of Data Warehousing and Mining (IJDWM), 3 (2). pp. 67-82. ISSN 1548-3924

Barker, Gary C., Talbot, Nicola L. C. and Peck, Mike W. (2002) Risk assessment for Clostridium botulinum: a network approach. International Biodeterioration & Biodegradation, 50 (3-4). pp. 167-175. ISSN 0964-8305

Bescoby, D.J, Cawley, GC and Chroston, N (2006) Enhanced interpretation of magnetic survey data from archaeological sites using artificial neural networks. Geophysics, 71 (5). pp. 45-53. ISSN 1942-2156

Bescoby, D.J, Cawley, GC and Chroston, N (2004) Enhanced interpretation of magnetic survey sata using artificial neural networks: A case study from Butrint, Southern Albania. Archaeological Prospection, 11. pp. 189-199. ISSN 1099-0763

Bescoby, DJ, Cawley, GC and Chroston, PN (2003) Interpretation of geophysical surveys of archaeological sites using artificial neural networks. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

Bosson, A., Cawley, G. C., Chan, Y. and Harvey, R. W. (2002) Non-retrieval: blocking pornographic images. In: Image and Video Retrieval. Lecture Notes in Computer Science, 2383 . Springer Berlin / Heidelberg, pp. 50-60. ISBN 978-3-540-43899-1

C

Cawley, G and Janacek, GJ (2010) On allometric equations for predicting body mass of dinosaurs. Journal of Zoology, 280 (4). pp. 355-361. ISSN 0952-8369

Cawley, G. C and Talbot, N. L. C (2007) Agnostic learning versus prior knowledge in the design of kernel machines. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks (IJCNN-2007), 2007-08-12 - 2007-08-17.

Cawley, G. C. (2006) Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN-2006), 2006-10-01.

Cawley, G. C. (2007) Model selection for kernel probit regression. In: Proceedings of the European Symposium on Artificial Neural Networks, 2007-04-25 - 2007-04-27.

Cawley, G. C. (2000) On a fast, compact approximation of the exponential function. Neural Computation, 12 (9). pp. 2009-2012. ISSN 1530-888X

Cawley, G. C., Janacek, G. J. and Talbot, N. L. C. (2007) Generalised Kernel Machines. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, 2007-01-01.

Cawley, G. C. and Talbot, N. L. C. (2003) Efficient leave-one-out cross-validation of kernel Fisher discriminant classifiers. Pattern Recognition, 36 (11). pp. 2585-2592. ISSN 0031-3203

Cawley, G. C. and Talbot, N. L. C. (2004) Efficient model selection for kernel logistic regression. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR-2004), 2004-08-23 - 2004-08-26.

Cawley, G. C. and Talbot, N. L. C. (1996) Fast index assignment algorithm for vector quantisation over noisy transmission channels. IEE Electronics Letters, 32 (15). pp. 1343-1344. ISSN 0013-5194

Cawley, G. C. and Talbot, N. L. C. (2002) Improved sparse least-squares support vector machines. Neurocomputing, 48 (1-4). pp. 1025-1031. ISSN 0925-2312

Cawley, G. C. and Talbot, N. L. C. (2002) Reduced rank kernel ridge regression. Neural Processing Letters, 16 (3). pp. 293-302. ISSN 1370-4621

Cawley, G. C., Talbot, N. L. C. and Girolami, M. (2007) Sparse multinomial logistic regression via Bayesian L1 regularisation. In: Advances in Neural Information Processing Systems. MIT Press, pp. 209-216. ISBN 9780262195683

Cawley, G.C., Cowtan, K., Way, R.G., Jacobs, P. and Jokimäki, A. (2015) On a minimal model for estimating climate sensitivity. Ecological Modelling, 297. pp. 20-25. ISSN 0304-3800

Cawley, G.C. and Talbot, N.L.C. (2014) Kernel learning at the first level of inference. Neural Networks, 53. pp. 69-80. ISSN 0893-6080

Cawley, GC, Janacek, GJ, Haylock, MR and Dorling, SR (2007) UNSPECIFIED In: UNSPECIFIED Elsevier, pp. 537-549.

Cawley, GC and Talbot, NLC (2008) Efficient approximate leave-one-out cross-validation for kernel logistic regression. Machine Learning, 71 (2-3). pp. 243-264.

Cawley, GC and Talbot, NLC (2006) Gene selection in cancer classification using sparse logistic regression with Bayesian regularisation. Bioinformatics, 22 (19). pp. 2348-2355. ISSN 1367-4803

Cawley, GC and Talbot, NLC (2010) On over-fitting in model selection and subsequent selection bias in performance evaluation. Journal of Machine Learning Research, 11. pp. 2079-2107. ISSN 1533-7928

Cawley, GC and Talbot, NLC (2007) Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters. Journal of Machine Learning Research, 8. pp. 841-861. ISSN 1533-7928

Cawley, GC and Talbot, NLC (2005) The evidence framework applied to sparse kernel logistic regression. Neurocomputing, 64. pp. 119-135. ISSN 0925-2312

Cawley, GC, Talbot, NLC, Janacek, GJ and Peck, MW (2006) Sparse Bayesian kernel survival analysis for modeling the growth domain of microbial pathogens. IEEE Transactions on Neural Networks, 17 (2). pp. 471-481. ISSN 1045-9227

Cawley, Gavin C. and Dorling, Stephen R. (1996) Reproducing a Subjective Classification Scheme for Atmospheric Circulation Patterns over the United Kingdom using a Neural Network. In: International Conference on Artificial Neural Networks (ICANN-96), 1996-01-01.

Cawley, Gavin C. and Talbot, Nicola L. C. (2005) Constructing Bayesian formulations of sparse kernel learning methods. Neural Networks, 18 (5-6). pp. 674-683. ISSN 0893-6080

Cawley, Gavin C. and Talbot, Nicola L. C. (2004) Fast exact leave-one-out cross-validation of sparse least-squares support vector machines. Neural Networks, 17 (10). pp. 1467-1475. ISSN 0893-6080

Cawley, Gavin C. and Talbot, Nicola L. C. (2001) Manipulation of prior probabilities in support vector classifications. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN-2001), 2001-07-16 - 2001-07-19.

Cawley, Gavin C. and Talbot, Nicola L. C. (2002) A greedy training algorithm for sparse least-squares support vector machines. In: Artificial Neural Networks — ICANN 2002. Lecture Notes in Computer Science, 2415 . Springer Berlin / Heidelberg, pp. 681-686. ISBN 978-3-540-44074-1

Cawley, Gavin C. and Talbot, Nicola L. C. (2005) A simple trick for constructing Bayesian formulations of sparse kernel learning methods. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN-2005), 2005-07-31 - 2005-08-04.

Cawley, Gavin C., Talbot, Nicola L. C., Foxall, Robert J., Dorling, Stephen R. and Mandic, Danilo P. (2004) Heteroscedastic kernel ridge regression. Neurocomputing, 57. pp. 105-124. ISSN 0925-2312

Cawley, Gavin C., Talbot, Nicola L. C., Janacek, Gareth J. and Peck, Mike W. (2004) Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis. In: Deterministic and Statistical Methods in Machine Learning. Lecture Notes in Computer Science, 3635 . Springer Berlin / Heidelberg, pp. 37-55.

Cox, Stephen J. and Cawley, Gavin C. (2003) The Use of Confidence Measures in Vector Based Call-Routing. In: 8th European Conference on Speech Communication and Technology (EUROSPEECH 2003), 2003-09-01 - 2003-09-04.

D

Dorling, Stephen R., Foxall, Robert J., Mandic, Danilo P. and Cawley, Gavin C. (2003) Maximum likelihood cost functions for neural network models of air quality data. Atmospheric Environment, 37 (24). pp. 3435-3443. ISSN 1352-2310

F

Farrash, Majed and Wang, Wenjia (2015) An Algorithm for Identifying the Learning Patterns in Big Data. In: IEEE Conference on Big Data, 2015-08-20 - 2015-08-22.

Foxall, R. J., Cawley, G. C. and Peck, M. W. (2003) Modelling the growth domain of Clostridium botulinum via kernel survival analysis. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

Foxall, RJ, Cawley, GC, Dorling, SR and Mandic, DP (2002) Error functions for prediction of episodes of poor air quality. In: Proceedings of the International Confernce on Artificial Neural Networks. Springer, pp. 1031-1036.

G

Guile, G., Rae, S., Young, A. and Wang, W. (2006) What can we learn from follow-up DEXA scans? Osteoporosis International, 17 (4). p. 422. ISSN 0937-941X

Guile, G. and Wang, W. (2008) Boosting for feature selection for microarray data analysis. In: Proceedings of IEEE WCCI-IJCNN08, 2008-01-01.

Guile, G. and Wang, W. (2007) Enhancing Boosting by Feature Non-Replacement for Microarray Data Analysis. In: International Joint Conference on Neural Networks, 2007-08-12 - 2007-08-17.

Guyon, Isabelle, Cawley, Gavin, Bennett, Kristin, Jair Escalente, Hugo, Escalera, Sergio, Ho, Tin Kam, Macia, Nuria, Ray, Bisakha, Saeed, Mehreen, Statnikov, Alexander and Viegas, Evelyne (2015) UNSPECIFIED In: UNSPECIFIED IEEE Press.

H

Harrison, Richard, Birchall, Roger, Mann, Dave and Wang, Wenjia (2012) Novel consensus approaches to the reliable ranking of features for seabed imagery classification. International Journal of Neural Systems, 22 (6). ISSN 0129-0657

K

Kukkonen, J, Partanen, L, Karppinen, A, Ruuskanen, J, Junninen, H, Kolehmainen, M, Niska, H, Dorling, S, Foxall, R and Cawley, G (2003) Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki. Atmospheric Environment, 37 (32). pp. 4539-4550.

L

Lan, Y., Cawley, G. C. and Harvey, R. W. (2003) Train-spotting: building classifiers for microarrays. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

Li, Q, Macgregor, AJ and Wang, W (2011) Novel Data Mining Approaches for Detecting Quantitative Trait Loci of Bone Mineral Density in Genome-Wide Linkage Analysis. In: Intelligent Data Engineering and Automated Learning - IDEAL 2011. Springer, pp. 498-510.

Lucas, S., Zhao, Z., Cawley, G. C. and Noakes, P. D. (1993) Pattern recognition with the decomposed multilayer perceptron. IEE Electronics Letters, 29 (5). pp. 442-443. ISSN 0013-5194

M

Mace, A, Sommariva, R, Fleming, Z and Wang, W (2011) Adaptive K-Means for Clustering Air Mass Trajectories. In: Intelligent Data Engineering and Automated Learning - IDEAL 2011. Spring, pp. 1-8.

Mace, Alex and Wang, Wenjia (2015) Modelling the role of catastrophe, crossover and Katanin in the self organisation of cortical microtubules. IET Systems Biology. ISSN 1751-8849 (Submitted)

Mace, Alex and Wang, Wenjia (2015) Modelling the role of catastrophe, crossover and Katanin in the self organisation of cortical microtubules. IET Systems Biology, 9 (6). pp. 277-284. ISSN 1751-8849

Mojahed, Aalaa, Bettencourt-Silva, Joao H., Wang, Wenjia and de la Iglesia, Beatriz (2015) Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF). In: Machine Learning and Data Mining in Pattern Recognition. Lecture Notes in Computer Science, 9166 . Springer International Publishing, pp. 251-265. ISBN 978-3-319-21023-0

R

Richards, G., Brazier, K. J. and Wang, W. (2006) Feature Salience Definition and Estimation and its Use in Feature Subset Selection. Intelligent Data Analysis, 10 (1). pp. 3-21. ISSN 1088-467X

Richards, G. and Wang, W. (2006) Investigations on the Characteristics of Random Decision Tree Ensembles. In: IEEE Proceedings of the International Joint Conference on Neural Networks (IJCNN '06), 2006-07-16 - 2006-07-21.

Richards, Graeme and Wang, Wenjia (2012) What influences the accuracy of decision tree ensembles? Journal of Intelligent Information Systems, 39 (3). pp. 627-650. ISSN 0925-9902

S

Saadi, K, Talbot, NLC and Cawley, GC (2007) Optimally regularised kernal Fisher discriminant classification. Neural Networks, 20 (7). pp. 832-841. ISSN 0893-6080

Saadi, K., Lee, K. K., Cawley, G. C. and Bevan, M. W. (2005) Predicting sugar regulation in Arabidopsis thaliana using kernel learning methods. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN-2005), 2005-07-31 - 2005-08-04.

Saadi, K., Talbot, N. L. C. and Cawley, G. C. (2004) Optimally regularised kernel Fisher discriminant analysis. In: Proceedings of the 17th International Conference on Pattern Recognition (ICPR-2004), 2004-08-23 - 2004-08-26.

Saeed, Awat, Cawley, Gavin and Bagnall, Anthony (2015) Benchmarking the Semi-Supervised Naïve Bayes Classifier. In: The International Joint Conference on Neural Networks, 2015-07-12 - 2015-07-17.

Schlink, U, Herbarth, O, Richter, M, Dorling, S, Nunnari, G, Cawley, G and Pelikan, E (2006) Statistical models to assess the health effects and to forecast ground-level ozone. Environmental Modelling and Software, 21 (4). pp. 547-558. ISSN 1873-6726

Steil, J. J., Cawley, G. C. and Villmann, T. (2005) Trends in Neurocomputing at ESANN 2004. Neurocomputing, 64. pp. 1-4.

T

Talbot, Nicola L. C. and Massara, R. E. (1997) Quadratic assignment algorithm that takes module size into account. IEE Electronics Letters, 33 (14). pp. 1201-1203. ISSN 0013-5194

Taylor, D., Cawley, G. and Hayward, S. (2014) Quantitative method for the assignment of hinge and shear mechanism in protein domain movements. Bioinformatics, 30 (22). pp. 3189-3196. ISSN 1367-4803

Taylor, Daniel, Cawley, Gavin and Hayward, Steven (2013) Classification of Protein Domain Movements using Dynamic Contact Graphs. PLoS ONE, 8 (11). ISSN 1932-6203

Theobald, B, Bangham, JA, Matthews, I and Cawley, GC (2004) Near-videorealistic synthetic talking faces: Implementation and evaluation. Speech Communication, 44 (1-4). pp. 127-140. ISSN 0167-6393

Theobald, B, Bangham, JA, Matthews, I and Cawley, GC (2002) Towards video realistic synthetic visual speech. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP- 2002), 2002-05-13 - 2002-05-17.

Theobald, B, Cawley, G, Bangham, A and Matthews, I (2008) Comparing text-driven and speech-driven visual speech synthesisers. In: INTERSPEECH, 2011-01-01.

Theobald, BJ, Cawley, GC, Matthews, I and Bangham, JA (2003) Near-videorealistic synthetic visual speech using non-rigid appearance models. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '03), 2003-04-06 - 2003-04-10.

Theobald, BJ, Kruse, SM, Bangham, JA and Cawley, GC (2003) Towards a low bandwidth talking face using appearance models. Image and Vision Computing, 21 (13-14). pp. 1117-1124. ISSN 0262-8856

Theobald, Barry, Cox, Stephen, Cawley, Gavin and Milner, Ben (1999) Fast Method of Channel Equalisation for Speech Signals and its Implementation on a DSP. IEE Electronics Letters, 35 (16). pp. 1309-1311. ISSN 0013-5194

W

Waddams Price, Catherine, Brazier, Karl and Wang, Wenjia (2012) Objective and subjective measures of fuel poverty. Energy Policy, 49. pp. 33-39. ISSN 0301-4215

Wang, W. (2002) Quantifying Relevance of Input Features. In: Intelligent Data Engineering and Automated Learning — IDEAL 2002 Third International Conference Manchester, UK, August 12–14, 2002 Proceedings. Lecture Notes in Computer Science, 2412 . Springer Berlin / Heidelberg, pp. 685-695. ISBN 978-3-540-44025-3

Wang, W. and Brunn, P. (2000) An effective genetic algorithm for job shop scheduling. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 214 (4). pp. 293-300. ISSN 0954-4054

Wang, W. and Rae, S. (2005) Intelligent Ensemble System Aids Osteoporosis Early Detection. WSEAS Transaction on Systems, 4 (4). pp. 455-560.

Wang, W., Rae, S. and Richards, G. (2006) Hybrid Data Mining Ensemble for Identifying Osteoporosis Risk Factors and Likelihood. Osteoporosis International, 17. p. 409. ISSN 0937-941X

Wang, Wenjia, Jones, Phillis and Partridge, Derek (2000) Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems. In: Multiple Classifier Systems. Lecture Notes in Computer Science, 1857 . Springer Berlin / Heidelberg, pp. 240-249. ISBN 978-3-540-67704-8

Y

Yli-Harja, O, Koivisto, P, Bangham, JA, Cawley, GC, Harvey, RW and Shmulevich, I (2001) Simplified implementation of the recursive median sieve. Signal Processing, 81 (7). pp. 1565-1570. ISSN 0165-1684

Z

Zhang, GL, Ansari, HR, Rahman, H, Cawley, G, Hertz, T, Hue, X, Jojic, N, Kim, Y, Kohlbacher, O, Lund, O, Lundegaardi, C, Magaret, CA, Nielsen, M, Papadopoulos, H, Raghava, GPS, Tal, VS, Xue, LC, Yanover, C, Zhu, S, Rock, MT, Crowe, JE, Panayiotou, C, Polycarpou, MM, Ducho, W and Brusic, V (2011) Machine learning competition in immunology – Prediction of HLA class I binding peptides. Journal of Immunological Methods, 374 (1-2). pp. 1-4. ISSN 0022-1759

Zhang, Lei, Fisher, Mark and Wang, Wenjia (2015) UNSPECIFIED In: UNSPECIFIED IEEE Press, pp. 952-956.

Zhang, Lei, Fisher, Mark and Wang, Wenjia (2014) Comparative performance of Texton based vascular tree segmentation in retinal images. In: IEEE Int. Conf. on Image Processing (ICIP'2014), 2014-10-28 - 2014-10-30, Paris.

Zhang, Lei, Fisher, Mark and Wang, Wenjia (2014) Retinal vessel segmentation using Gabor Filter and Textons. In: Medical Image Understanding and Analysis (MIUA 2014), 2014-07-09 - 2014-07-11, Royal Holloway College.

This list was generated on Sat Jan 19 00:22:35 2019 GMT.