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Professor Stephen Gunn

Academic Staff

Steve Gunn graduated from the University of Southampton in 1992 with a first class honours degree in Electronic Engineering. He obtained his PhD, from the University of Southampton in 1996. In 1996 he worked as a research fellow, in 1998 he became a lecturer, and in 2002 a senior lecturer in the Image, Speech and Intelligent Systems Research Group. In 2007 he was awarded a personal chair in the Information: Signals Images Systems Research Group at the University of Southampton.

His research covers two state-of-the-art areas, that of machine learning and computer vision. His work focuses on the development of techniques to convert these ill-posed inverse problems, to well-posed problems through the careful design of a function space with an appropriate prior.

His PhD work investigated the use of active contours (or 'snakes') to extract image boundaries. Active contour techniques use an energy minimisation framework to integrate prior generic constraints with the image data. The techniques differ significantly from conventional approaches in that they search for a local minimum. His work focussed on improving the robustness of active contours by considering the initialisation and parameterisation.

His recent research has involved the development of new machine learning algorithms based upon kernel methods and their application to a variety of domains. Kernel methods are rapidly replacing neural networks as the preferred tool for machine learning due to many attractive features: a strong basis from statistical learning theory; no computational penalty in moving from linear to non-linear models; the resulting optimisation problem is convex, guaranteeing a unique global solution and consequently producing systems with excellent generalisation performance, i.e. they learn extremely well.

His current research is focussed around the investigation of priors that induce a sparsity in a parameter space. This has advantages for learning in terms of speed, memory, representation and generalisation performance; these characteristics become increasingly important as larger data-sets are considered.

His interests include windsurfing, snowboarding, opera, reading and watching weather reports.

Research

Publications

Femminella, O.P., Starink, M.J., Gunn, S.R., Harris, C.J. and Reed, P.A.S. (2000) Neurofuzzy and SUPANOVA modelling of structure-property relationships in Al-Zn-Mg-Cu alloys. In, Aluminium Alloys: Their Physical and Mechanical Properties. 7th International Conference ICAA7 Switzerland, Trans Tech, 1255-1260. (Materials Science Forum 331-337).

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2000) Approaches to classification of imbalanced data - a case study on automotive materials. In, Sixth Postgraduate Conference in Engineering Materials, Southampton, UK, 06 Oct 2000. 2pp.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) A case study of SVM extension techniques on classification of imbalanced data. In, International Conference on Neural Networks and Applications, Puerto de la Cruz, Spain, , 309-314.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Control sensitivity SVM for imbalanced data a case study on automotive material. In, 5th International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA 2001), Prague, Czech Republic, 22 - 25 Apr 2001. 4pp.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Approaches to imbalanced data for classification: a case study. In, Proceedings of the International ICSC Congress on Computational Intelligence: Methods & Applications. International ICSC Congress on Computational Intelligence: Methods & Applications (CIMA 2001) Millet, Canada, ICSC Interdisciplinary Research.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Regression models for classification to enhance interpretability. In, Proceedings of the 3rd international conference on intelligent processing and manufacturing of materials (IPMM). 3rd International Conference Intelligent Processing and Manufacturing of Materials , Intelligent Processing and Manufacturing of Materials.

Christensen, S.W., Reed, P.A.S., Gunn, S.R. and Sinclair, I. (2002) Comparison of modelling techniques in the analysis of commercial materials data. In, Proceedings of Intelligent Processing and Manufacturing of Materials. IPMM-2001: The 3rd International Conference on Intelligent Processing and Manufacturing of Materials , IPMM, 49-58.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Classification of imbalanced data with transparent kernel. In, Proceedings of IJCNN '01. International Joint Conference on Neural Networks, 2001. IJCNN '01. International Joint Conference on Neural Networks, 2001 Piscataway, USA, Institute of Electrical and Electronics Engineers, 2410-2415. (doi:10.1109/IJCNN.2001.938744).

Reed, P.A.S., Thomson, R.C., James, J.S., Putman, D.C., Lee, K.K. and Gunn, S.R. (2003) Modelling of microstructural effects in the fatigue of austempered ductile iron. Materials Science and Engineering A, 346, (1-2), 273-286. (doi:10.1016/S0921-5093(02)00545-2).

Brown, Martin, Gunn, Steve R. and Lewis, Hugh G. (1999) Support vector machines for optimal classification and spectral unmixing. Ecological Modelling, 120, (2-3), 167-179. (doi:10.1016/S0304-3800(99)00100-3).

Brown, M., Lewis, H.G. and Gunn, S.R. (1999) Estimation of sub-pixel land cover using support vector methods. In, 25th Annual Conference and Exhibition of the Remote Sensing Society (RSS '99): From Data to Information, Cardiff, UK, 08 - 10 Sep 1999.

Brown, M., Lewis, H.G. and Gunn, S.R. (1999) Support vector machines for spectral unmixing. In, Proceedings of the IEEE 1999 International Symposium on Geoscience and Remote Sensing Symposium (IGARSS '99). EE 1999 International Symposium on Geoscience and Remote Sensing Symposium (IGARSS '99) Piscataway, USA, Institute of Electrical and Electronics Engineers, 1363-1365. (doi:10.1109/IGARSS.1999.774631).

Christensen, S., Kandola, J.S., Femminella, O., Gunn, S.R., Reed, P.A.S. and Sinclair, I. (2000) Adaptive numerical modelling of commercial aluminium plate performance. In, Starke, Jr., E.A., Sanders, T.H. and Cassada, W.A. (eds.) Aluminium Alloys: Their Physical and Mechanical Properties. 7th International Conference ICAA7 Switzerland, Trans Tech, 533-538. (Materials Science Forum 331-337).

Reed, P.A.S., Starink, M.J., Gunn, S.R. and Sinclair, I. (2009) Invited review: Adaptive numerical modelling and hybrid physically based ANM approaches in materials engineering - a survey. Materials Science and Technology, 25, (4), 488-503. (doi:10.1179/174328409X411727).

Brackstone, M.A. and Gunn, S. (1988) Quantum disordered spin models/bose condensation. In, Ando, T. and Fukuyama, H. (eds.) Anderson Localization. Proceedings of the International Symposium, Tokyo, Japan, August 16-18, 1987. London, GB, Springer, 130-133. (Springer Proceedings in Physics, 28).

Mohammad, M., Moore, E., Carter, J.N., Shadle, C.H. and Gunn, S.R. (1997) Using MRI to Image the Moving Vocal Tract during Speech. Eurospeech '97 , 2027--2030.

Brown, M., Gunn, S.R., Ng, C.Y. and Harris, C.J. (1997) Neurofuzzy Systems Modelling: A Transparent Approach. In, Warwick, K. (eds.) Dealing with Complexity: A Neural Network Approach. , Springer Verlag.

Gunn, S.R. and Nixon, M.S. (1997) A Robust Snake Implementation: A Dual Active Contour. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19, (1), 63--68.

Gunn, S.R., Brown, M. and Bossley, K.M. (1997) Network Performance Assessment for Neurofuzzy Data Modelling. Lecture Notes in Computer Science , 313--323.

Gunn, S.R. and Nixon, M.S. (1996) Snake Head Boundary Extraction using Local and Global Energy Minimisation. IEEE Int. Conf. on Pattern Recognition, Vienna, Austria, , 581-585.

Gunn, S.R. (1996) Dual Active Contour Models for Image Feature Extraction. University of Southampton, Electronics and Computer Science : University of Southampton, Doctoral Thesis .

Gunn, S.R. and Nixon, M.S. (1994) A Dual Active Contour Including Parameteric Shape.

Gunn, S.R. and Nixon, M.S. (1995) A Dual Active Contour for Improved Snake Performance.

Gunn, S.R. and Nixon, M.S. (1995) Improving Snake Performance via a Dual Active Contour. Computer Analysis of Images and Patterns, Prague, Czech Republic, Springer Verlag, 600-605.

Gunn, S.R. and Nixon, M.S. (1994) A Model Based Dual Active Contour. Proc. British Machine Vision Conference BMVA Press, 305-314.

Gunn, S.R. and Nixon, M.S. (1994) A Dual Active Contour for Head Boundary Extraction. Colloq. on Image Processing for Biometric Measurement , 6/1--6/4.

Gunn, S.R. and Nixon, M.S. (1994) A Dual Active Contour Incorporating Parametric Shape Description. European Signal Processing, Edinburgh, U.K., , 435-438.

Damper, R. I., Gunn, S. R. and Gore, M. O. (2000) Extracting phonetic knowledge from learning systems: Perceptrons, support vector machines and linear discriminants. Applied Intelligence, 12, (1-2), 43-62.

Damper, R. I. and Gunn, S. R. (1999) Learning phonetic distinctions from speech signals. Eurospeech'99, Budapest, Hungary, , 2675-2678.

Damper, R.I. and Gunn, S.R. (1998) On the learnability of the voicing contrast for initial stops. 5th International Conference on Spoken Language Processing, Sydney, Australia , 2143-2146.

Nixon, M. S., Ng, L. S., Benn, D. E. and Gunn, S. R. (1997) Considerations on extended feature vectors in automatic face recognition. IEEE International Conference on Systems, Man, and Cybernetics SMC 97 , 4075-4080.

Brown, M. and Gunn, S. R. (1998) Empirical data modelling algorithms: Additive spline models and support vector machines. UKACC Int. Conf. on Control '98

Gunn, S. R. and Nixon, M. S. (1998) Global and local active contours for head boundary extraction. International Journal of Computer Vision, 30, (1), 43-54.

Gunn, S. R. (1998) Edge detection error in the discrete laplacian of gaussian. IEEE International Conference on Image Processing, Chicago, U.S.A.,

Gunn, S. R. (1998) On the discrete representation of the laplacian of gaussian. Pattern Recognition, 32, (8), 1463-1472.

Gunn, S. R. and Brown, M. (1999) SUPANOVA - a sparse, transparent modelling approach. IEEE International Workshop on Neural Networks for Signal Processing, Madison, Wisconsin, , 21-30.

Chen, S., Gunn, S.R. and Harris, C.J. (2000) Decision feedback equalizer design using support vector machines. IEE Proceedings Vision, Image and Signal Processing, 147, (3), 213-219.

Gao, J.B., Harris, C.J. and Gunn, S.R. (2001) On a Class of Support Vector Kernels based on Frames in Function Hilbert Spaces. Neural Computation, 13, 1975-1994.

Femminella, O.P., Starink, M.J., Gunn, S.R., Harris, C.J. and Reed, P.A.S. (2000) Neurofuzzy and SUPANOVA Modelling of Structure-Property Relationships in Al-Zn-Mg-Cu Alloys. In, Starke, E.A., Sanders, T.H. and Cassada, W.A. (eds.) UNSPECIFIED Aluminium Alloys: Their Physical and Mechanical Properties , , 1255-1260.

Kandola, J.S., Gunn, S.R., Sinclair, I. and Reed, P.A.S. (1999) Data Driven Knowledge Extraction of Materials Properties. At Intelligent Processing and Manufacturing of Materials, Hawaii, U.S.A., , 361-366.

Christensen, S.W., Kandola, J.S., Femminella, O.P., Gunn, S.R., Reed, P.A.S. and Sinclair, I. (2000) Adaptive Numerical Modelling of Commercial Aluminium Plate Performance. In, Starke, E.A., Sanders, T.H. and Cassada, W.A. (eds.) Mater. Sci. Forum. Aluminium Alloys: Their Physical and Mechanical Properties , , 533-538.

Gao, J.B., Gunn, S.R., Harris, C.J. and Brown, M. (2002) A Probabilistic Framework for SVM Regression and Error Bar Estimation. Machine Learning, 46, 71-89.

Gao, J.B., Gunn, S.R., Harris, C.J. and Brown, M. (2001) Regression with Input-dependent Noise: a Relevance Vector Machine Treatment. IEEE Trans. Neural Networks

Shi, D., Gunn, S. R., Damper, R. I. and Shu, W. (2000) Recognition rule acquisition by an advanced extension matrix algorithm. Engineering Intelligent Systems for Electrical Engineering and Communications, 8, (2), 97-101.

Chen, S., Gunn, S.R. and Harris, C.J. (2001) The relevance vector machine technique for channel equalization application. IEEE Transactions on Neural Networks, 12, (6), 1529-1532.

Wilmer, A. I., Stathaki, T., Gunn, S. R. and Damper, R. I. (2001) Texture analysis with the Volterra model using conjugate gradient optimisation. At 9th European Symposium on Artificial Neural Networks, Bruges, Belgium, , 211-216.

Damper, R. I. and Gunn, S. R. (2001) Modeling the acoustic-to-auditory transformation for stop consonant-vowel syllables. Fifth International Conference on Cognitive and Neural Systems, Boston, MA, , #23.

Brown, M., Lewis, H.G. and Gunn, S.R. (1999) Support Vector Machines for Optimal Classification and Spectral Unmixing. Ecological Modelling, 120, 167--179.

Brown, M., Lewis, H.G. and Gunn, S.R. (1999) Linear Spectral Mixture Models and Support Vector Machines for Remote Sensing. IEEE Trans. Geoscience and Remote Sensing, 38, (5), 2346--2360.

Gunn, R.N., Gunn, S.R. and Cunningham, V.J. (2001) Positron Emission Tomography Compartmental Models. Journal of Cerebral Blood Flow and Metabolism, 21, (6), 635-652.

Kandola, J.S. (2001) Interpretable Modelling with Sparse Kernels. University of Southampton, Electronics and Computer Science : University of Southampton, Doctoral Thesis .

Shi, D., Gunn, S. R. and Damper, R. I. (2001) A radical approach to handwritten Chinese character recognition using active handwriting models. IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, , 670-675.

Shi, D., Gunn, S. R. and Damper, R. I. (2001) A comparison among radical approaches to handwritten Chinese character recognition. International Conference on Chinese Computing, , 213-219.

Gunn, R.N., Gunn, S.R., Turkheimer, F.E., Aston, J.A.D. and Cunningham, V.J. (2002) Tracer kinetic modeling via basis pursuit. Brain Imaging using PET Academic Press.

Christensen, S.W., Reed, P.A.S., Gunn, S.R. and Sinclair, I. (2001) Comparison of Modelling Techniques in the Analysis of Commercial Materials Data. Intelligent Processing and Manufacturing of Materials, Vancouver, Canada,

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Regression Models for classification to Enhance Interpretability. At Intelligent Processing and Manufacturing of Materials, Vancouver, Canada,

Lee, K.K., Gunn, S.R., Harris, C.J. and Reed, P.A.S. (2001) Classification of Imbalanced Data with Transparent Kernels. At INNS-IEEE Int. Joint Conf. on Neural Networks, Washington, DC, U.S.A., , 2410-2415.

Gao, J.B., Gunn, S.R. and Harris, C.J. (2001) A New Implementation for SVM Regression based on Mean Field Analysis. At Computational Intelligence for Modelling Control and Automation, Las Vegas, U.S.A.,

Chen, J.L., Gunn, S.R. and Nixon, M.S. (2001) A model-based image segmentation framework using labeled and unlabeled data. At Int. Conf. on Advanced Concepts For Intelligent Vision Systems, Baden-Baden, Germany, , 112-116.

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Control Sensitivity SVM for Imbalanced Data. At Int. Conf. Artificial Neural Networks and Genetic Algorithms, Prague, Czech Republic,

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) Approaches to Imbalanced Data for Classification: A Case Study. At Computational Intelligence Methods and Applications, Bangor, U.K.,

Lee, K.K., Harris, C.J., Gunn, S.R. and Reed, P.A.S. (2001) A Case Study of SVM Extension Techniques on Classification of Imbalanced Data. At Int. Conf. Neural Networks and Applications, Puerto de la Cruz, Canary islands, Spain, , 309-314.

Gao, J.B., Gunn, S.R. and Kandola, J.S. (2000) A Variational Approach for Adapting Kernels in Support Vector Regression. At Advances in Neural Information Processing Systems (NIPS13) Kernel Workshop, Breckenridge, CO, U.S.A.,

Kandola, J.S. and Gunn, S.R. (2000) Assessing the Stability of Advanced Transparent Modelling Techniques. At CRM Workshop on Combining and Selecting Models using Machine Learning Algorithms, Montreal, Canada,

Chen, J.L., Gunn, S.R., Nixon, M.S., Myers, R.P. and Gunn, R.N. (2000) A Supervised Method for PET Reference Region Extraction. Medical Image Understanding and Analysis, London, U.K., , 179-182.

Gao, J.B., Harris, C.J., Gunn, S.R. and Brown, M. (2000) The error bar estimation for soft classification with Gaussian process models. ICSC Second Int. Symp. Neural Computation, Berlin, Germany,

Gunn, S.R. (1999) SUPANOVA - A Sparse, Transparent Modelling Approach. Advances in Neural Information Processing Systems (NIPS12) Kernel Workshop, Breckenridge, CO, U.S.A.,

Chen, J.L., Gunn, S.R., Nixon, M.S. and Gunn, R.N. (2001) Markov Random Field Models for Segmentation of PET Images. At Information Processing in Medical Imaging Springer, 468.

Gunn, S.R. (2000) Modelling with Support Vector Machines. Lecture Notes on Iterative Identification and Control Design , 289--321.

Gunn, S.R. and Kandola, J.S. (2002) Structural Modelling with Sparse Kernels. Machine Learning, 48, (1), 137-163.

Gunn, S.R. (1998) Support Vector Machines for Classification and Regression.

Gunn, S.R. (2001) Project Special Brew: Supercomputing on a budget.

Shi, D., Gunn, S. R. and Damper, R. I. (2003) Handwritten Chinese radical recognition using nonlinear active shape models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, (2), 277-280.

Shi, D., Gunn, S. R. and Damper, R. I. (2002) Handwritten Chinese character recognition using nonlinear active shape models and the Viterbi algorithm. Pattern Recognition Letters, 23, (14), 1853-1862.

Shi, D. (2002) An Active Radical Approach to Handwritten Chinese Character Recognition. University of Southampton, Electronics and Computer Science : Faculty of Engineering and Applied Science, Doctoral Thesis .

Ng, G. S., Shi, D., Gunn, S. R. and Damper, R. I. (2003) Nonlinear active handwriting models and their applications to handwritten Chinese radical recognition. At Seventh International Conference on Document Analysis and Recognition (ICDAR'03), Edinburgh., UK,

Gao, J.B., Gunn, S.R. and Kandola, J.S. (2002) Adapting Kernels by Variational Approach in SVM. In, 15th Australian Joint Conference on Artificial Intelligence, Canberra, Australia, Springer, 395-406.

Gao, J.B., Gunn, S.R. and Harris, C.J. (2003) Mean Field Method for the Support Vector Machine Regression. Neurocomputing, 50, 391-405.

Gao, J.B., Gunn, S.R. and Harris, C.J. (2003) SVM Regression through Variational Methods and its Sequential Implementation. Neurocomputing, 55, (1-2), 151-167.

Reed, P.A.S., Thomson, R.C., James, J.S., Putman, D.C., Lee, K.K. and Gunn, S.R. (2003) Modelling of Microstructural Effects in the Fatigue of Austempered Ductile Iron. Materials Science and Engineering, A436, 273-286.

Gunn, R.N., Gunn, S.R., Turkheimer, F.E., Aston, J.A.D. and Cunningham, V.J. (2002) Positron emission tomography compartmental models: A basis pursuit strategy for kinetic modelling. Journal of Cerebral Blood Flow and Metabolism, 22, (12), 1425-1439.

Christensen, S.W., Reed, P.A.S., Gunn, S.R. and Sinclair, I. (2002) Comparison of Modelling Techniques in the Analysis of Commercial Materials Data. In, Meech, J.A., Veiga, M.M., Kawazoe, Y. and LeClair, S.R. (eds.) Intelligence in a Materials World. , CRC Press, 49-58.

Lee, K.K. (2002) Classification of Imbalanced Data with Transparent Kernels. University of Southampton, Electronics and Computer Science, Doctoral Thesis .

Shi, D., Damper, R. I. and Gunn, S. R. (2003) Off-line handwritten Chinese character recognition by radical decomposition. ACM Transactions on Asian Language Processing, 2, (1), 27-48.

Al-Mazeed, Ahmad H., Nixon, Mark S. and Gunn, Steve R. (2003) Fusing Complementary Operators to Enhance Foreground/Background Segmentation. In, British Machine Vision Conference 2003, Norwich, BMVA Press, 501-510.

Dutta, Partha S., Dasmahapatra, Srinandan, Gunn, Steve R., Jennings, N. R. and Moreau, Luc (2004) Cooperative Information Sharing to Improve Distributed Learning. In, The AAMAS 2004 workshop on Learning and Evolution in Agent-Based Systems, New York, 19 - 24 Jul 2004. , 18-23.

Al-Mazeed, A. H., Nixon, M. S. and Gunn, S. R. (2004) Classifiers Combination for Improved Motion Segmentation. At International Conference on Image Analysis and Recognition, Porto, Portugal, 29 Sep - 01 Oct 2004. Springer-Verlag Heidelberg, 363-371.

Shi, D., Ng, G. S., Damper, R. I. and Gunn, S. R. (2005) Radical recognition of handwritten Chinese characters using GA-based kernel active shape modelling. IEE Proceedings: Vision, Image and Signal Processing, 152, (5), 634-638.

Guo, B., Gunn, S. R., Damper, R. I. and Nelson, J. (2005) Adaptive band selection for hyperspectral image fusion using mutual information. At 8th International Conference on Information Fusion, Philadelphia, PA, , 630-637.

Guo, B., Gunn, S. R., Damper, R. I. and Nelson, J. (2005) Hyperspectral image fusion using spectrally weighted kernels. At 8th International Conference on Information Fusion, Philadelphia, PA, , 402-408.

Turkheimer, F.E., Hinz, R., Gunn, R.N., Aston, J.A.D., Gunn, S.R. and Cunningham, V.J. (2003) Rank-Shaping Regularization of Exponential Spectral Analysis for Application to Functional Parametric Mapping. Physics in Medicine and Biology, 48, (23), 3819-3841.

Guyon, I.M., Gunn, S.R., Nikravesh, M. and Zadeh, L. (eds.) (2006) Feature Extraction, Foundations and Applications, Springer

Guyon, I.M., Gunn, S.R., Ben-Hur, A. and Dror, G. (2004) Result Analysis of the NIPS 2003 Feature Selection Challenge. At Advances in Neural Information Processing Systems, Vancouver, B.C., Canada,

Pearce, C.B., Gunn, S.R., Ahmed, A. and Johnson, C.D. (2004) Investigation of the use of machine learning in predicting severity in acute pancreatitis. At 11th Joint Meeting of the International Association of Pancreatology

Rogers, J.D. and Gunn, S.R. (2004) Ensemble Algorithms for Feature Selection. At Sheffield Machine Learning Workshop

Yang, J. and Gunn, S.R. (2004) Input Uncertainty in Support Vector Machines. At Sheffield Machine Learning Workshop

Pearce, C.B., Gunn, S.R., Ahmed, A. and Johnson, C.D. (2004) The use of machine learning techniques to predict severity in acute pancreatitis. At Digestive Disease Week 2004, New Orleans, U.S.A.,

Pearce, C.B., Gunn, S.R., Ahmed, A. and Johnson, C.D. (2004) Using machine learning to predict severity in acute pancreatitis. At British Society of Gastroenterology

Rogers, J.D. and Gunn, S.R. (2005) Identifying Feature Relevance using a Random Forest. At Subspace, Latent Structure and Feature Selection techniques: Statistical and Optimisation perspectives Workshop, Bohinj, Slovenia,

Saunders, C.J., Gunn, S.R., Grobelnik, M. and Shawe-Taylor, J. (eds.) (2006) Subspace, Latent Structure and Feature Selection techniques, Springer

Pearce, C.B., Gunn, S.R., Ahmed, A. and Johnson, C.D. (2006) Machine Learning Can Improve Prediction of Severity in Acute Pancreatitis using Admission Values of APACHE II Score and C-Reactive Protein. Pancreatology, 6, 123-131.

Guo, B., Gunn, S. R., Damper, R. I. and Nelson, J. D. B. (2006) Band selection for hyperspectral image classification using mutual information. IEEE Geoscience and Remote Sensing Letters, 3, (4), 522-526.

Nelson, J. D. B., Damper, R. I., Gunn, S. R. and Guo, B. (2006) Signal theory for SVM kernel parameter estimation. At IEEE International Workshop on Machine Learning for Signal Processing, Maynooth, Ireland, , 149-154.

Dhanjal, Charanpal, Gunn, Steve R. and Shawe-Taylor, John (2006) Sparse Feature Extraction using Generalised Partial Least Squares. In, IEEE International Workshop on Machine Learning for Signal Processing, Maynooth, Ireland, , 27-32.

Guo, B., Damper, R. I., Gunn, S. R. and Nelson, J. D. B. (2008) A fast separability-based feature selection method for high-dimensional remotely-sensed image classification. Pattern Recognition, 41, (5), 1670-1679. (doi:10.1016/j.patcog.2007.11.007).

Guo, B., Gunn, S. R., Damper, R. I. and Nelson, J. D. B. (2008) Customizing kernel functions for SVM-based hyperspectral image classification. IEEE Transactions on Image Processing, 17, (4), 622-629. (doi:10.1109/TIP.2008.918955).

Nelson, J. D. B., Damper, R. I., Gunn, S. R. and Guo, B. (2008) Signal theory for SVM kernel design with applications to parameter estimation and sequence kernels. Neurocomputing, 72, (1-3), 15-22. (doi:10.1016/j.neucom.2008.01.034).

Nelso, James D.B., Damper, Robert I., Gunn, Steve R. and Guo, Baofeng (2009) A signal theory approach to support vector classification: the sinc kernel. Neural Networks, 22, (1), 49-57. (doi:10.1016/j.neunet.2008.09.016). (PMID:19118976).

Dhanjal, Charanpal, Gunn, Steve and Shawe-Taylor, John (2009) Efficient sparse kernel feature extraction based on partial least squares. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, (8), 1347-1361. (doi:10.1109/TPAMI.2008.171).

Acharyya, Amit, Maharatna, Koushik, Al-Hashimi, Bashir and Gunn, Steve (2009) Memory Reduction Methodology for Distributed-Arithmetic-Based DWT/IDWT Exploiting Data Symmetry. IEEE Transactions on Circuits and Systems- II: Express Briefs, 56, (4), 285-289.

Acharyya, Amit, Maharatna, Koushik, Sun, Jinhong, Al-Hashimi, Bashir and Gunn, Steve (2009) Hardware Efficient Fixed-Point VLSI Architecture for 2D Kurtotic FastICA. At 19th European Conference on Circuit Theory and Design , Antalya, Turkey, 23 - 27 Aug 2009. , 165-168.

Pasupa, Kitsuchart, Saunders, Craig, Szedmak, Sandor, Klami, Arto, Kaski, Samuel and Gunn, Steve (2009) Learning to Rank Images from Eye Movements. At Proceeding of 2009 IEEE 12th International Conference on Computer Vision (ICCV'2009) Workshop on Human-Computer Interaction (HCI'2009), Kyoto, Japan, 27 Sep - 04 Oct 2009. IEEE, 2009-2016.

Klami, Arto, Kaski, Samuel, Pasupa, Kitsuchart, Szedmak, Sandor, Gunn, Steve, Hardoon, David and Csurka, Gabriela (2009) Predicting relevance of parts of an image.

Pasupa, Kitsuchart, Saunders, Craig, Szedmak, Sandor, Gunn, Steve, Hardoon, David, Klami, Arto, Kaski, Samuel, Leung, Alex and Auer, Peter (2009) Ranking algorithms for implicit feedback.

Reed, PAS, Starink, MJ, Gunn, SR and Sinclair, I (2009) Adaptive numerical modelling and hybrid physically based ANM approaches in materials engineering - a survey. MATERIALS SCIENCE AND TECHNOLOGY, 25, 488-503.

Lovell, Chris, Jones, Gareth, Gunn, Steve and Zauner, Klaus-Peter (2010) Autonomous Experimentation: Coupling Active Learning with Computer Controlled Microfluidics (abstract). At Active Learning and Experimental Design Workshop, Sardinia, Italy,

Acharyya, Amit, Tudugalle, Hasitha, Maharatna, Koushik, Al-Hashimi, Bashir and Gunn, Steve (2010) VLSI ARCHITECTURE FOR FETAL ECG EXTRACTION FOR PERSONALIZED HEALTHCARE APPLICATION WITHIN RESOURCE CONSTRAINED ENVIRONMENT. At Sixth UK Embedded Forum, University of Newcastle-upon-Tyne, United Kingdom, 30 Jun - 01 Jul 2010.

Lovell, Chris, Jones, Gareth, Gunn, Steve and Zauner, Klaus-Peter (2010) Characterising Enzymes for Information Processing: Towards an Artificial Experimenter. In, 9th International Conference on Unconventional Computation. , Springer Berlin / Heidelberg, 81-92.

Lovell, Chris, Jones, Gareth, Gunn, Steve and Zauner, Klaus-Peter (2010) An Artificial Experimenter for Enzymatic Response Characterisation. In, 13th International Conference on Discovery Science. , Springer-Verlag, 42-56.

Mahmoodi, Sasan and Gunn, Steve (2011) Scale Space Smoothing, Image Feature Extraction and Bessel Filters. At Lecture Notes in Computer Science-17th Scandinavian Conference on Image Analysis, Ystad, Sweden, 23 - 27 May 2011. Springer-Verlag, 625-634.

Mahmoodi, Sasan and Gunn, Steve (2011) Snake based Unsupervised Texture Segmentation using Gaussian Markov Random Field Models. At 18th IEEE International Conference on Image Processing , Brussels, Belgium, 11 - 14 Sep 2011. IEEE.

Lovell, Chris, Jones, Gareth, Gunn, Steve and Zauner, Klaus-Peter (2011) Autonomous Experimentation: Active Learning for Enzyme Response Characterisation. JMLR: Workshop and Conference Proceedings, 16, 141-155.

Lovell, Chris, Zauner, Klaus-Peter and Gunn, Steve (2011) Exploration and Exploitation in an Artificial Experimenter. In, ICML Workshop on On-line Trading of Exploration and Exploitation 2

Lovell, Chris, Jones, Gareth, Zauner, Klaus-Peter and Gunn, Steve R., Glowacka, Dorota, Dorard, Louis and Shawe-Taylor, John (eds.) (2012) Exploration and exploitation with insufficient resources. [in special issue: Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, July 2, 2011, Bellevue, Washington, USA] JMLR: Workshop and Conference Proceedings, 26, 37-61.

Wood, Alex L., Merrett, Geoff V., Gunn, Steve R., Al-Hashimi, Bashir M., Shadbolt, Nigel R and Hall, Wendy (2012) Adaptive sampling in context-aware systems: a machine learning approach. In, IET Wireless Sensor Systems 2012, London, GB, 18 - 19 Jun 2012. 5pp.

Lovell, Chris and Gunn, Steve (2012) Towards Improved Theoretical Problems for Autonomous Discovery. IEEE WCCI IJCNN 2012

Jones, Gareth, Lovell, Chris, Gunn, Steve, Morgan, Hywel and Zauner, Klaus-Peter (2012) Enabling the Discovery of Computational Characteristics of Enzyme Dynamics. IEEE WCCI CEC 2012

Ghosh, Shaona, Lovell, Christopher James and Gunn, Steve R. (2013) Towards pareto descent directions in sampling experts for multiple tasks in an on-line learning paradigm. In, Proceedings of the AAAI Spring Symposium Series of Lifelong Machine Learning 2013. Palo Alto, US, AAAI Press. (AAAI Spring Symposium Series, SS-13-05, 13 5).

Ghosh, Shaona and Gunn, Steve (2012) Towards potential-based learning for pareto trade-offs in on-line prediction with experts. At Women in Machine Learning 2012, Lake Tahoe, Nevada, USA, 03 Dec 2012.

Ghosh, Shaona, Lovell, Christopher James and Gunn, Steve R. (2013) Towards pareto descent directions in sampling experts for multiple tasks in an on-line learning paradigm. At AAAI Spring Symposium on Lifelong Machine Learning 2013, Stanford, US, 25 - 27 Mar 2013.

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