Items where School is "Machine learning in computational biology

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Al Shaqsi, Jamil and Wang, Wenjia (2013) Estimating the predominant number of clusters in a dataset. Intelligent Data Analysis, 17 (4). pp. 603-626. ISSN 1088-467X

Aldehim, Ghadah and Wang, Wenjia (2017) Determining appropriate approaches for using data in feature selection. International Journal of Machine Learning and Cybernetics, 8 (3). 915–928. ISSN 1868-808X

Aldehim, Ghadah and Wang, Wenjia (2014) Reliability and Effectiveness of Cross-validation in Feature Selection. In: Thirty-fourth SGAI International Conference on Artificial Intelligence, 2014-12-09 - 2014-12-11, Peterhouse College.

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

Alharbi, Najmah, Zhou, Ji and Wang, Wenjia (2018) Automatic Counting of Wheat Spikes from Wheat Growth Images. In: 7th International Conference on Pattern Recognition Applications and Methods. SCITEPRESS – Science and Technology Publications, PRT, pp. 346-355. ISBN 978-989-758-276-9

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 2015 (International Conference on Data Science and Advanced Analytics);, 2015-10-19 - 2015-10-21.

Alqurashi, Tahani and Wang, Wenjia (2019) A Novel Adaptive Clustering Ensemble Method. International Journal of Machine Learning and Cybernetics, 10 (6). pp. 1227-1246. ISSN 1868-8071

Alqurashi, Tahani and Wang, Wenjia (2014) Object-Neighbourhood based Clustering Ensemble Method. In: The 15th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2014), 2014-09-09 - 2014-09-12.

Alshaqsi, Jamil and Wang, Wenjia (2013) A Hybrid Method for Estimating the Predominant Number of Clusters in a Data Set. In: Proceedings of the 11th International Conference on Machine Learning and Applications (ICMLA). IEEE Press, GBR. ISBN 978-1-4673-4651-1

Alyahyan, Saleh, Farrash, Majed and Wang, Wenjia (2016) Heterogeneous Ensemble for Imaginary Scene Classification. In: Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR. UNSPECIFIED, POL, pp. 197-204. ISBN 978-989-758-203-5

Alyahyan, Saleh and Wang, Wenjia (2018) Decision level ensemble method for classifying multi-media data. Wireless Networks. ISSN 1022-0038

Alyahyan, Saleh and Wang, Wenjia (2017) Feature Level Ensemble Method for Classifying Multi-Media Data. In: International Conference on Innovative Techniques and Applications of Artificial Intelligence. Lecture Notes in Computer Science . Springer, GBR, pp. 235-249. ISBN 978-3-319-71077-8

Bagnall, A, Cawley, G, Whittley, I, Bull, L, Studley, M, Pettipher, M and Tekiner, F (2008) Super Computer Heterogeneous Classifier Meta-Ensembles. In: Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications. IGI Global, pp. 1320-1333. ISBN 978-1599049519

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, Anthony J., Cawley, Gavin C., Whittley, Ian M., Bull, Larry, Studley, Matthew, Pettipher, Mike 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

Ballard, Chris and Wang, Wenjia (2016) Dynamic ensemble selection methods for heterogeneous data mining. In: 12th World Congress on Intelligent Control and Automation (WCICA), 2016. IEEE Press, CHN. ISBN 978-1-4673-8415-5

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.

Bian, S. and Wang, W. (2007) Ensemble Classification System Implementation for Biomedical Data. In: Life Science Data Mining. Science, Engineering, and Biology Informatics, 2 . World Science Publishers,, pp. 239-256. ISBN 978-981-270-064-3

Bian, S. and Wang, W. (2006) Investigation on Diversity in Homogeneous and Heterogeneous Ensembles. In: International Joint Conference on Neural Networks, 2006-07-16 - 2006-07-21.

Bian, Shun and Wang, Wenjia (2007) On diversity and accuracy of homogeneous and heterogeneous ensembles. International Journal of Hybrid Intelligent Systems, 4 (2). pp. 103-128. ISSN 1448-5869

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, GBR, pp. 50-60. ISBN 978-3-540-43899-1

Cawley, G (2011) Baseline Methods for Active Learning. In: JMLR: Workshop and Conference Proceedings 16. JMLR Workshop and Conference Proceedings, 16 . Microtome, pp. 47-57.

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. (2009) Causal & non-causal feature selection for ridge regression. In: Journal of Machine Learning Research: Workshop and Conference Proceedings, 2008-06-01 - 2008-06-06.

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. (2001) Model selection for support vector machines via adaptive step-size tabu search. In: International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA-2001), 2001-04-01.

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. and Talbot, N. L. C. (2004) Sparse Bayesian kernel logistic regression. In: Proceedings of the European Symposium on Artificial Neural Networks (ESANN-2004), 2004-04-28 - 2004-04-30.

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. (2001) Efficient sequential minimal optimisation of support vector classifiers. In: International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA-2001), 2001-04-01.

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 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 (2010) Some Baseline Methods for the Active Learning Challenge. In: Thirteenth International Conference on Artificial Intelligence and Statistics. Workshop and Active Learning Competition, 2010-05-16.

Cawley, Gavin C. (1996) An Improved Vector Quantisation Algorithm for Speech Transmission Over Noisy Channels. In: International Conference on Spoken Language Processing (ICSLP-96), 1996-10-01.

Cawley, Gavin C., Cowtan, Kevin, Way, Robert G., Jacobs, Peter and Jokimäki, Ari (2015) On a minimal model for estimating climate sensitivity. Ecological Modelling, 297. pp. 20-25. ISSN 0304-3800

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. (2003) Efficient cross-validation of kernel Fisher discriminant classifiers. In: Proceedings of the European Symposium on Artificial Neural Networks (ESANN-2003), 2003-04-23 - 2003-04-25.

Cawley, Gavin C. and Talbot, Nicola L. C. (2002) Efficient formation of a basis in a kernel induced feature space. In: European Symposium on Artificial Neural Networks (ESANN 2002), 2002-04-24 - 2002-04-26.

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, ESP, 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., 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.

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.

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.

Guile, G. and Wang, W. (2008) Relationships between depth of decision tree and boosting performance. In: Proceedings of IEEE WCCI-IJCNN08, 2008-01-01.

Guyon, I, Cawley, G, Dror, G and Lemaire, V (2011) Results of the Active Learning Challenge. In: Workshop on Active Learning and Experimental Design. JMLR Workshop and Conference Proceedings, 16 . Microtome, pp. 19-45.

Guyon, I, Saffari, A, Dror, G and Cawley, G (2010) Model selection: Beyond the Bayesian/frequentist divide. Journal of Machine Learning Research, 11. pp. 61-87. ISSN 1533-7928

Guyon, I., Cawley, G., Dror, G. and Lemaire, V. (2010) Design and Analysis of the WCCI 2010 Active Learning Challenge. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks (IJCNN-2010), 2010-07-18 - 2010-07-23.

Guyon, I., Saffari, A., Dror, G. and Cawley, G. C. (2007) Agnostic learning vs. prior knowledge challenge. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks (IJCNN-2007), 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) Design of the 2015 ChaLearn AutoML challenge. In: Proceedings of International Joint Conference on Neural Networks (IJCNN). IEEE Press.

Guyon, Isabelle, Saffari, Amir, Dror, Gideon and Cawley, Gavin (2008) Analysis of the IJCNN 2007 agnostic learning versus prior knowledge challenge. Neural Networks, 21 (2-3). pp. 544-550.

Harrison, R, Birchall, R, Mann, D and Wang, W (2011) A Novel Ensemble of Distance Measures for Feature Evaluation: Application to Sonar Imagery. In: Intelligent Data Engineering and Automated Learning - IDEAL 2011. Springer, pp. 327-336.

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

Haylock, MR, Cawley, GC, Harpham, C, Wilby, RL and Goodess, CM (2006) Downscaling heavy precipitation over the United Kingdom: A comparison of dynamical and statistical methods and their future scenarios. International Journal of Climatology, 26 (10). pp. 1397-1415. ISSN 1097-0088

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.

Lee, K. K., Cawley, G. C. and Bevan, M. W. (2005) Sparse Bayesian promoter based gene classification. In: Proceedings of the European Symposium on Artificial Neural Networks (ESANN-2005), 2005-04-27 - 2005-04-29.

Li, Yunhai, Lee, Kee Khoon, Walsh, Sean, Smith, Caroline, Hadingham, Sophie, Sorefan, Karim, Cawley, Gavin C. and Bevan, Michael W. (2006) Establishing glucose- and ABA-regulated transcription networks in Arabidopsis by microarray analysis and promoter classification using a Relevance Vector Machine. Genome Research, 16 (3). pp. 414-427. ISSN 1088-9051

Lines, Jason A., Bagnall, Anthony, Caiger-Smith, Patrick and Anderson, Simon (2011) Classification of Household Devices by Electricity Usage Profiles. Proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning. pp. 403-412.

Lucas, S, Zhao, Z, Cawley, GC and Noakes, PD (1993) On decomposing MLPs. In: IEEE International Conference on Neural Networks (ICNN-93), 1993-01-01.

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

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

Mohammed, Rekar O. and Cawley, Gavin C. (2017) Over-Fitting in Model Selection with Gaussian Process Regression. In: Machine Learning and Data Mining in Pattern Recognition. Lecture Notes in Computer Science, 10358 (1). Springer, pp. 192-205. ISBN 978-3-319-62415-0

Partridge, D., Wang, W. and Jones, P. (2000) Artificial intelligence techniques for software system enhancement. In: International ICSC Congress on Intelligent Systems and Applications, 2000-01-01.

Partridge, D., Wang, W. and Jones, P. (2001) Efficient and Effective Feature Selection in the Presence of Feature Interaction and Noise. In: Advances in Pattern Recognition — ICAPR 2001. Lecture Notes in Computer Science, 2013 . Springer Berlin / Heidelberg, BRA, pp. 196-201. ISBN 978-3-540-41767-5

Rae, S. and Wang, W. (2002) Predicting osteoporosis from risk factors with data mining ensembles. In: International Osteoporosis Foundation: World Congress on Osteoporosis, 2002-05-10 - 2002-05-14.

Richards, G., Brazier, K. and Wang, W. (2005) The Definition and Estimation of Feature Salience in Databases. In: Conference on Databases and Applications, 2005-02-14 - 2005-02-16.

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

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., Cawley, G. C. and Talbot, N. L. C. (2002) Fast exact leave-one-out cross-validation of least-square support vector machines. In: European Symposium on Artificial Neural Networks (ESANN-2002), 2002-04-24 - 2002-04-26.

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.

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

Talbot, Nicola L. C. and Cawley, Gavin C. (1997) A Fast Index Assignment Method for Robust Vector Quantisation of Image Data. In: I.E.E.E. International Conference on Image Processing (ICIP-97), 1997-10-26 - 1997-10-29.

Talbot, Nicola L. C. and Cawley, Gavin C. (1996) A Quadratic Index Assignment Algorithm for Vector Quantisation over Noisy Transmission Channels. In: Institute of Acoustics Autumn Conference (Speech and Hearing 96), 1996-01-01.

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

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, Bangham, JA, Matthews, I and Cawley, GC (2001) Visual speech synthesis using statistical models of shape and appearance. In: International Conference on Auditory-Visual Speech Processing (AVSP-2001), 2001-09-07 - 2001-09-09.

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, B, Cawley, GC, Glauert, JRW, Abider, JA and Matthews, I (2003) 2.5D Visual Speech Synthesis Using Appearance Models. In: British Machine Vision Conference, 2005-09-05 - 2005-09-08.

Theobald, B-J, Bangham, JA, Matthews, I and Cawley, GC (2003) Evaluating talking heads based on appearance models. In: Proceedings of the International Conference on Auditory-Visual Speech Processing (AVSP-2003), 2003-09-04 - 2003-09-07.

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, Bangham, J. Andrew, Kruse, Silko, Cawley, Gavin and Matthews, Iain (2001) Towards videorealistic synthetic visual speech. In: Uncertainty in Geometric Computations. The Kluwer International Series in Engineering and Computer Science, 704 . Kluwer Academic Publishers, pp. 175-184. ISBN 978-0-7923-7309-4

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

Wainer, Jacques and Cawley, Gavin (2017) Empirical evaluation of resampling procedures for optimising SVM hyperparameters. Journal of Machine Learning Research, 18 (15). pp. 1-35. ISSN 1532-4435

Wang, M, Wang, Wenjia and Abeywardane, A. (2013) Autoimmune haemolytic anaemia after allogeneic haematopoietic stem cell transplantation: analysis of 555 transplant patients at King’s College Hospital. In: The 53rd Annual Scientific Meeting of the British Society for Haematology, 2013-04-20.

Wang, W. (2001) Identifying Salient Risk Factors by Clamping Neural Networks. In: IASTED International Conference on Artificial Intelligence and Applications, 2001-09-01.

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 Cao-Thai, P. (2008) Novel Position coded methods for mining and ranking web access patterns. In: Conference on Intelligence and Security Informatics, 2008-01-01.

Wang, W., Jones, P. and Partridge, D. (2000) Assessing the impact of input features in a feedforward network. Neural Computing & Applications, 19 (2). pp. 101-112. ISSN 0941-0643

Wang, W., Jones, P. and Partridge, D. (2000) Identification of Feature-Salience. In: The IEEE-INNS-ENNS, International Joint Conference on Neural Networks (IJCNN 2000), 2000-07-24 - 2000-07-27.

Wang, W., Jones, P. and Partridge, D. (2001) A comparative study of feature-salience ranking techniques. Neural Computation, 13 (7). pp. 1603-1623. ISSN 0899-7667

Wang, W. and Partridge, D. (2000) Multiversion systems of neural networks and decision trees. In: IASTED International Conference on Neural Networks (NN'2000), 2000-05-15 - 2000-05-17.

Wang, W., Partridge, D. and Etherington, J. (2001) Hybrid Ensembles and Coincident-Failure Diversity. In: International Joint Conference on Neural Networks (IJCNN '01), 2001-07-15 - 2001-07-19.

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 (2007) Diversity and Accuracy of Data Mining Ensemble. In: Life Science Data Mining. Science, Engineering, and Biology Informatics, 2 . World Science Publishers, pp. 47-72. ISBN 978-981-270-064-3

Wang, Wenjia and Farrash, Majed (2013) How data partitioning strategies influence the performance of ensemble in big data mining? In: IEEE Int. Conference on Big Data, 2013-10-06 - 2013-10-10.

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, ITA, pp. 240-249. ISBN 978-3-540-67704-8

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

Zhang, Guang Lan, Ansari, Hifzur Rahman, Bradley, Phil, Cawley, Gavin C., Hertz, Tomer, Hue, Xihao, Jojic, Nebojsa, Kim, Yohan, Kohlbacher, Oliver, Lund, Ole, Lundegaardi, Claus, Magaret, Craig A., Nielsen, Morten, Papadopoulos, Harris, Raghava, G. P. S., Tal, Vider-Shalit, Xue, Li C., Yanover, Chen, Zhu, Shanfeng, Rock, Michael T., Crowe, James E., Panayiotou, Christos, Polycarpou, Marios M., Ducho, Włodzisław and Brusic, Vladimir (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 (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 (2015) Comparative performance of Texton based vascular tree segmentation in retinal images. In: 2014 IEEE International Conference on Image Processing (ICIP). IEEE Press, FRA, pp. 952-956.

Zhang, Lei, Fisher, Mark and Wang, Wenjia (2013) Locating blood vessels in retinal images using unified Textons. In: the 17th Annual Conference in Medical Image Understanding and Analysis (MIUA), 2013-07-10.

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 Mon Mar 23 16:46:11 2020 GMT.