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Number of items: 400.

Article

(2013) Smooth operators. 30th International Conference on Machine Learning, ICML 2013 (PART 3) pp. 2221-2229.

(2012) Data dependent kernels in nearly-linear time. Journal of Machine Learning Research , 22 pp. 685-693.

(2011) Improved loss bounds for multiple kernel learning. Journal of Machine Learning Research , 15 pp. 370-377. Gold open access

(2006) Kernel methods: A paradigm for pattern analysis. pp. 1-39. 10.4018/978-1-59904-042-4.ch001.

Ajanki, A; Hardoon, DR; Kaski, S; Puolamaki, K; Shawe-Taylor, J; (2009) Can eyes reveal interest? Implicit queries from gaze patterns. USER MODELING AND USER-ADAPTED INTERACTION , 19 (4) pp. 307-339. 10.1007/s11257-009-9066-4.

Ajanki, A; Hardoon, DR; Kaski, S; Puolamaki, K; Shawe-Taylor, J; (2009) Can eyes reveal interest? Implicit queries from gaze patterns. USER MODELING AND USER-ADAPTED INTERACTION , 19 (4) pp. 307-339. 10.1007/s11257-009-9066-4.

Ambroladze, A; Parrado-Hernandez, E; Shawe-Taylor, J; (2007) Complexity of pattern classes and the Lipschitz property. THEORETICAL COMPUTER SCIENCE , 382 (3) pp. 232-246. 10.1016/j.tcs.2007.03.047.

Anthony, M; Bartlett, PL; Ishai, Y; Shawe-Taylor, J; (1996) Valid Generalisation from Approximate Interpolation. Combinatorics, Probability & Computing , 5 pp. 191-214.

Anthony, M; Brightwell, GR; Shawe-Taylor, J; (1995) On Specifying Boolean Functions by Labelled Examples. Discrete Applied Mathematics , 61 (1) pp. 1-25.

Anthony, M; Shawe-Taylor, J; (1997) A Sufficient Condition for Polynomial Distribution-dependent Learnability. Discrete Applied Mathematics , 77 (1) pp. 1-12.

Anthony, M; Shawe-Taylor, J; (1994) A Result of Vapnik with Applications. Discrete Applied Mathematics , 52 (2) p. 211.

Anthony, M; Shawe-Taylor, J; (1993) A Result of Vapnik with Applications. Discrete Applied Mathematics , 47 (3) pp. 207-217.

Anthony, M; Shawe-Taylor, J; (1993) Using the Perceptron Algorithm to Find Consistent Hypotheses. Combinatorics, Probability & Computing , 2 pp. 385-387.

Archambeau, C; Cornford, D; Opper, M; Shawe-Taylor, J; (2007) Gaussian Process Approximations of Stochastic Differential Equations. Gaussian Processes in Practice , 1 pp. 1-16.

Auer, P; Hussain, Z; Kaski, S; Klami, A; Kujala, J; Laaksonen, J; Leung, AP; ... Shawe-Taylor, J; + view all (2010) Pinview: Implicit Feedback in Content-Based Image Retrieval. PROCEEDINGS OF THE FIRST WORKSHOP ON APPLICATIONS OF PATTERN ANALYSIS , 11 pp. 51-57.

Bennett, KP; Cristianini, N; Shawe-Taylor, J; Wu, D; (2000) Enlarging the Margins in Perceptron Decision Trees. Machine Learning , 41 (3) pp. 295-313.

Best, K; Oakes, T; Heather, JM; Shawe-Taylor, J; Chain, B; (2015) Computational analysis of stochastic heterogeneity in PCR amplification efficiency revealed by single molecule barcoding. Scientific Reports , 5 , Article 14629. 10.1038/srep14629. Green open access
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Biggs, N; Boshier, A; Shawe-Taylor, J; (1986) Cubic Distance-regular Graphs. Journal of the London Mathematical Society , 33 (2) pp. 385-394.

Bridle, S; Balan, ST; Bethge, M; Gentile, M; Harmeling, S; Heymans, C; Hirsch, M; ... Wittman, D; + view all (2010) Results of the GREAT08 Challenge: an image analysis competition for cosmological lensing. MON NOT R ASTRON SOC , 405 (3) 2044 - 2061. 10.1111/j.1365-2966.2010.16598.x.

Bridle, S; Balan, ST; Bethge, M; Gentile, M; Harmeling, S; Heymans, C; Hirsch, M; ... Wittman, D; + view all Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing. 10.1111/j.1365-2966.2010.16598.x.

Bridle, S; Shawe-Taylor, J; Amara, A; Applegate, D; Balan, ST; Berge, J; Bernstein, G; ... Wittman, D; + view all (2009) HANDBOOK FOR THE GREAT08 CHALLENGE: AN IMAGE ANALYSIS COMPETITION FOR COSMOLOGICAL LENSING. ANN APPL STAT , 3 (1) 6 - 37. 10.1214/08-AOAS222.

Buntine, W; Grobelnik, M; Mladenić, D; Shawe-Taylor, J; (2009) Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009 Bled, Slovenia, September 7-11, 2009 Proceedings, Part I - Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 5781 L (PART 1)

Burge, P; Shawe-Taylor, J; (2001) An Unsupervised Neural Network Approach to Profiling the Behavior of Mobile Phone Users for Use in Fraud Detection. J. Parallel Distrib. Comput. , 61 (7) pp. 915-925.

Burge, P; Shawe-Taylor, J; (1995) Adapting the Energy Landscape for MFA. Journal of Artificial Neural Networks , 2 (4) pp. 449-454.

Burge, P; Shawe-Taylor, J; (1995) Bitstream Neurons for Graph Colouring. Journal of Artificial Neural Networks , 2 (4) pp. 443-448.

Chen, H; Cheng, T; Shawe-Taylor, J; (2017) A Balanced Route Design for Min-Max Multiple-Depot Rural Postman Problem (MMMDRPP): a police patrolling case. International Journal of Geographical Information Science 10.1080/13658816.2017.1380201. (In press). Green open access
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Chisholm, S; Stein, AB; Jordan, NR; Hubel, TM; Shawe-Taylor, J; Fearn, T; McNutt, JW; ... Hailes, S; + view all (2019) Parsimonious test of dynamic interaction. Ecology and Evolution , 9 (4) pp. 1654-1664. 10.1002/ece3.4805. Green open access
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Cinelli, M; Sun, Y; Best, K; Heather, JM; Reich-Zeliger, S; Shifrut, E; Friedman, N; ... Chain, B; + view all (2017) Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires. Bioinformatics , 33 (7) pp. 951-955. 10.1093/bioinformatics/btw771. Green open access
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Cohen, D; Shawe-Taylor, J; (1990) Daugman's Gabor transform as a simple generative back-propagation network. Electronics Letters , 26 (16) pp. 1241-1243.

Cousins, S; Shawe-Taylor, J; (2017) High-probability minimax probability machines. Machine Learning , 106 (6) pp. 863-886. 10.1007/s10994-016-5616-2. Green open access
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Cristianini, N; Shawe-Taylor, J; Lodhi, H; (2002) Latent Semantic Kernels. J. Intell. Inf. Syst. , 18 (2-3) pp. 127-152.

Cristianini, N; Shawe-Taylor, J; Williamson, R; (2001) Introduction to the Special Issue on Kernel Methods (Kernel Machines Section). Journal of Machine Learning Research , 2 (2) pp. 95-96. Gold open access

Daalen, M; Jeavons, P; Shawe-Taylor, J; Cohen, D; (1993) A Device for Generating Binary Sequences for Stochastic Computing. Electronics Letters , 29 (1) pp. 80-81.

Daalen, M; Kosel, T; Jeavons, P; Shawe-Taylor, J; (1994) Emergent activation functions from a stochastic bit stream neuron. Electronics Letters , 30 (4) pp. 331-333.

Demiriz, A; Bennett, K; Shawe-Taylor, J; (2001) Linear Programming Boosting via Column Generation. Machine Learning , 46 (1) pp. 225-254.

Demiriz, A; Bennett, KP; Shawe-Taylor, J; (2002) Linear Programming Boosting via Column Generation. Machine Learning , 46 (1-3) pp. 225-254.

Dhanjal, C; Gunn, SR; Shawe-Taylor, J; (2009) Efficient Sparse Kernel Feature Extraction Based on Partial Least Squares. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 31 (8) pp. 1347-1361. 10.1109/TPAMI.2008.171.

Dhanjal, C; Gunn, SR; Shawe-Taylor, J; (2009) Efficient sparse kernel feature extraction based on partial least squares. IEEE Trans Pattern Anal Mach Intell , 31 (8) pp. 1347-1361. 10.1109/TPAMI.2008.171.

Diethe, T; Durrant, S; Shawe-Taylor, J; Neubauer, H; (2009) Detection of changes in patterns of brain activity according to musical tonality. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009 pp. 12-17.

Diethe, T; Hardoon, DR; Shawe-Taylor, J; (2010) Constructing Nonlinear Discriminants from Multiple Data Views. MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT I , 6321 pp. 328-343.

Dolia, A; Harris, C; Shawe-Taylor, J; Titterington, M; (2007) Kernal Ellipsoid Trimming. Computational Statistics and Data Analysis , 52 (1) pp. 309-324.

Dorard, L; Shawe-Taylor, J; (2010) Gaussian Process Bandits for Tree Search. CoRR , abs/10

Durrant, S; Hardoon, DR; Brechmann, A; Shawe-Taylor, J; Miranda, ER; Scheich, H; (2009) GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. CONNECTION SCIENCE , 21 (2-3) pp. 161-175. 10.1080/09540090902733863.

Durrant, S; Hardoon, DR; Brechmann, A; Shawe-Taylor, J; Miranda, ER; Scheich, H; (2009) GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison (vol 21, pg 161, 2009). CONNECTION SCIENCE , 21 (4) p. 383. 10.1080/09540090903132230.

Durrant, S; Hardoon, DR; Brechmann, A; Shawe-Taylor, J; Miranda, ER; Scheich, H; (2009) GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. CONNECTION SCIENCE , 21 (2-3) pp. 161-175. 10.1080/09540090902733863.

Fletcher, T; Hussain, Z; Shawe-Taylor, J; (2010) Multiple Kernel Learning on the Limit Order Book. PROCEEDINGS OF THE FIRST WORKSHOP ON APPLICATIONS OF PATTERN ANALYSIS , 11 pp. 167-174.

Fletcher, T; Shawe-Taylor, J; (2013) Multiple Kernel Learning with Fisher Kernels for High Frequency Currency Prediction. COMPUTATIONAL ECONOMICS , 42 (2) pp. 217-240. 10.1007/s10614-012-9317-z.

Fletcher, T; Shawe-Taylor, J; (2012) Multiple Kernel Learning with Fisher Kernels for High Frequency Currency Prediction. Computational Economics pp. 1-24.

Foss, A; Shawe-Taylor, J; Whitworth, D; (1972) Search for a Trans-Plutonian Planet. Nature , 239 (5370)

Furl, N; Kumar, S; Alter, K; Durrant, S; Shawe-Taylor, J; Griffiths, TD; (2011) Neural prediction of higher-order auditory sequence statistics. NEUROIMAGE , 54 (3) pp. 2267-2277. 10.1016/j.neuroimage.2010.10.038.

Gillies, M; Pan, X; Slater, M; Shawe-Taylor, J; (2008) Responsive listening behavior. COMPUT ANIMAT VIRT W , 19 (5) 579 - 589. 10.1002/cav.267.

Glowacka, D; Dorard, L; Medlar, A; Shawe-Taylor, J; (2011) Prior Knowledge in Learning Finite Parameter Spaces. FORMAL GRAMMAR , 5591 pp. 199-213.

Glowacka, D; Shawe-Taylor, J; (2010) Content-based Image Retrieval with Multinomial Relevance Feedback. PROCEEDINGS OF 2ND ASIAN CONFERENCE ON MACHINE LEARNING (ACML2010) , 13 pp. 111-125.

Glowacka, D; Shawe-Taylor, J; Clark, A; de la Higuera, C; Johnson, M; (2011) Introduction to the Special Topic on Grammar Induction, Representation of Language and Language Learning. JOURNAL OF MACHINE LEARNING RESEARCH , 12 pp. 1425-1428. Gold open access

Godsil, CD; Shawe-Taylor, J; (1987) Distance-regularised graphs are distance-regular or distance-biregular. J. Comb. Theory, Ser. B , 43 (1) pp. 14-24.

Graepel, T; Herbrich, R; (2005) PAC-Bayesian compression bounds on the prediction error of learning algorithms for classification. MACHINE LEARNING , 59 (1-2) pp. 55-76. 10.1007/s10994-005-0462-7.

Grünewälder, S; Broekhuis, F; Macdonald, DW; Wilson, AM; McNutt, JW; Shawe-Taylor, J; Hailes, S; (2012) Movement activity based classification of animal behaviour with an application to data from cheetah (Acinonyx jubatus). PLoS One , 7 (11) , Article e49120. 10.1371/journal.pone.0049120. Green open access
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Guan, N; Tao, D; Luo, Z; Shawe-Taylor, J; (2012) MahNMF: Manhattan Non-negative Matrix Factorization. CoRR , abs/12

Guo, Y; Bartlett, PL; Shawe-Taylor, J; Williamson, RC; (2002) Covering numbers for support vector machines. IEEE Trans. Information Theory , 48 (1) pp. 239-250.

Hall, BX; Shawe-Taylor, J; Johnston, A; (2011) Employing The Complete Face in AVSR to Recover from Facial Occlusions. WAPA , 17 pp. 33-40.

Hardoon, DR; Mourao-Miranda, J; Brammer, M; Shawe-Taylor, J; (2007) Unsupervised analysis of fMRI data using kernel canonical correlation. NEUROIMAGE , 37 (4) 1250 - 1259. 10.1016/j.neuroimage.2007.06.017.

Hardoon, DR; Mourão-Miranda, J; Brammer, M; Shawe-Taylor, J; (2007) Unsupervised analysis of fMRI data using kernel canonical correlation. NeuroImage , 37 (4) pp. 1250-1259. 10.1016/j.neuroimage.2007.06.017.

Hardoon, DR; Shawe-Taylor, J; (2011) Sparse canonical correlation analysis. MACHINE LEARNING , 83 (3) pp. 331-353. 10.1007/s10994-010-5222-7.

Hardoon, DR; Shawe-Taylor, J; (2010) Decomposing the tensor kernel support vector machine for neuroscience data with structured labels. MACHINE LEARNING , 79 (1-2) pp. 29-46. 10.1007/s10994-009-5159-x.

Hardoon, DR; Shawe-Taylor, J; (2010) Decomposing the tensor kernel support vector machine for neuroscience data with structured labels. Machine Learning , 79 (1-2) pp. 29-46. 10.1007/s10994-009-5159-x.

Hardoon, DR; Shawe-Taylor, J; (2009) Convergence analysis of kernel Canonical Correlation Analysis: theory and practice. MACHINE LEARNING , 74 (1) pp. 23-38. 10.1007/s10994-008-5085-3.

Hardoon, DR; Shawe-Taylor, J; (2009) Convergence analysis of kernel Canonical Correlation Analysis: theory and practice. MACHINE LEARNING , 74 (1) pp. 23-38. 10.1007/s10994-008-5085-3.

Hardoon, DR; Szedmák, S; Shawe-Taylor, J; (2004) Canonical Correlation Analysis: An Overview with Application to Learning Methods. Neural Computation , 16 (12) pp. 2639-2664.

Haworth, J; Cheng, T; Shawe-Taylor, J; Wang, J; (2014) Local online kernel ridge regression for forecasting of urban travel times. Transportation Research Part C: Emerging Technologies , 46 151 - 178. 10.1016/j.trc.2014.05.015. Green open access
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Higgs, M; Shawe-Taylor, J; (2010) A PAC-Bayes Bound for Tailored Density Estimation. ALGORITHMIC LEARNING THEORY, ALT 2010 , 6331 pp. 148-162.

Hussain, Z; Laviolette, F; Marchand, M; Shawe-Taylor, J; Brubaker, SC; Mullin, MD; (2007) Revised loss bounds for the set covering machine and sample-compression loss bounds for imbalanced data. J MACH LEARN RES , 8 2533 - 2549. Gold open access

Hussain, Z; Pasupa, K; Shawe-Taylor, J; (2010) Learning relevant eye movement feature spaces across users. Eye Tracking Research and Applications Symposium (ETRA) pp. 181-186. 10.1145/1743666.1743711.

Hussain, Z; Shawe-Taylor, J; (2011) A Note on Improved Loss Bounds for Multiple Kernel Learning. CoRR , abs/11

Hussain, Z; Shawe-Taylor, J; Hardoon, DR; Dhanjal, C; (2011) Design and Generalization Analysis of Orthogonal Matching Pursuit Algorithms. IEEE TRANSACTIONS ON INFORMATION THEORY , 57 (8) pp. 5326-5341. 10.1109/TIT.2011.2158880.

Jeavons, P; Cohen, DA; Shawe-Taylor, J; (1994) Generating binary sequences for stochastic computing. IEEE Trans. Information Theory , 40 (3) pp. 716-720.

Kandola, J; Hofmann, T; Poggio, T; Shawe-Taylor, J; (2003) Introduction to the Special Issue on Machine Learning Methods for Text and Images. Journal of Machine Learning Research , 3 pp. 1023-1024. Gold open access

Kempinska, K; Longley, P; Shawe-Taylor, J; (2018) Interactional regions in cities: making sense of flows across networked systems. International Journal of Geographical Information Science , 32 (7) pp. 1348-1367. 10.1080/13658816.2017.1418878. Green open access
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Kim, JY; Shawe-Taylor, J; (1994) Fast Expected string Machine using an n-gram Algorithm. Software: Practice and Experience , 24 pp. 79-88.

Kim, JY; Shawe-Taylor, J; (1994) Fast String Matching using an n -gram Algorithm. Softw., Pract. Exper. , 24 (1) pp. 79-88.

Kim, JY; Shawe-Taylor, J; (1992) An Approximate String-Matching Algorithm. Theor. Comput. Sci. , 92 (1) pp. 107-117.

Kitching, T; Amara, A; Gill, M; Harmeling, S; Heymans, C; Massey, R; Rowe, B; ... Wittman, D; + view all (2011) GRAVITATIONAL LENSING ACCURACY TESTING 2010 (GREAT10) CHALLENGE HANDBOOK. ANNALS OF APPLIED STATISTICS , 5 (3) pp. 2231-2263. 10.1214/11-AOAS484.

Kolcz, A; Mladenic, D; Buntine, W; Grobelnik, M; Shawe-Taylor, J; (2009) Guest editors' introduction: special issue of selected papers from ECML PKDD 2009. DATA MINING AND KNOWLEDGE DISCOVERY , 19 (2) pp. 173-175. 10.1007/s10618-009-0143-4.

Kolcz, A; Mladenic, D; Buntine, W; Grobelnik, M; Shawe-Taylor, J; (2009) Guest editors' introduction: Special Issue from ECML PKDD 2009. MACHINE LEARNING , 76 (2-3) pp. 175-177. 10.1007/s10994-009-5138-2.

Law, T; Shawe-Taylor, J; (2017) Practical Bayesian support vector regression for financial time series prediction and market condition change detection. Quantitative Finance , 17 (9) pp. 1403-1416. 10.1080/14697688.2016.1267868. Green open access
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Lehtinen, S; Lees, J; Bähler, J; Shawe-Taylor, J; Orengo, C; (2015) Gene Function Prediction from Functional Association Networks Using Kernel Partial Least Squares Regression. PLoS One , 10 (8) , Article e0134668. 10.1371/journal.pone.0134668. Green open access
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Lever, G; Diethe, T; Shawe-Taylor, J; (2012) Data dependent kernels in nearly-linear time. AISTATS , 22 pp. 685-693.

Lever, G; Laviolette, F; Shawe-Taylor, J; (2013) Tighter PAC-Bayes bounds through distribution-dependent priors. THEORETICAL COMPUTER SCIENCE , 473 pp. 4-28. 10.1016/j.tcs.2012.10.013.

Lever, G; Laviolette, F; Shawe-Taylor, J; (2013) Tighter PAC-Bayes bounds through distribution-dependent priors. Theoretical Computer Science , 473 pp. 4-28. 10.1016/j.tcs.2012.10.013.

Li, S; Shawe-Taylor, J; (2005) Comparison and fusion of multiresolution features for texture classification. Pattern Recognition Letters , 26 (5) pp. 633-638.

Li, Y; Shawe-Taylor, J; (2007) Advanced learning algorithms for cross-language patent retrieval and classification. INFORMATION PROCESSING & MANAGEMENT , 43 (5) pp. 1183-1199. 10.1016/j.ipm.2006.11.005.

Li, Y; Shawe-Taylor, J; (2006) Using KCCA for Japanese-English cross-language information retrieval and document classification. J. Intell. Inf. Syst. , 27 (2) pp. 117-133.

Liu, C-A; Weng, C-W; Spectral Radius of Bipartite Graphs.

Lodhi, H; Karakoulas, GI; Shawe-Taylor, J; (2002) Boosting strategy for classification. Intell. Data Anal. , 6 (2) pp. 149-174.

Lodhi, H; Saunders, C; Shawe-Taylor, J; Cristianini, N; Watkins, CJCH; (2002) Text Classification using String Kernels. Journal of Machine Learning Research , 2 pp. 419-444. Gold open access

Marchand, M; Shawe-Taylor, J; (2002) The Set Covering Machine. Journal of Machine Learning Research , 3 pp. 723-746. Gold open access

Michie, S; Thomas, J; Johnston, M; Mac Aonghusa, P; Shawe-Taylor, J; Kelly, MP; Deleris, LA; ... West, R; + view all (2017) The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation. Implementation Science , 12 , Article 121. 10.1186/s13012-017-0641-5. Green open access
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Mohar, B; Pisanski, T; Shawe-Taylor, J; (1981) Edge-colouring of Composite Regular Graphs. Colloquia Mathematica Societatis J?nos Bolyai , 37 pp. 591-600.

Mohar, B; Shawe-Taylor, J; (1985) Distance-biregular graphs with 2-valent vertices and distance-regular line graphs. J. Comb. Theory, Ser. B , 38 (3) pp. 193-203.

Monteiro, JM; Rao, A; Shawe-Taylor, J; Mourao-Miranda, J; (2016) A multiple hold-out framework for Sparse Partial Least Squares. Journal of Neuroscience Methods , 271 pp. 182-194. 10.1016/j.jneumeth.2016.06.011. Green open access
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Mourao-Miranda, J; Hardoon, DR; Hahn, T; Marquand, AF; Williams, SCR; Shawe-Taylor, J; Brammer, M; (2011) Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine. NEUROIMAGE , 58 (3) 793 - 804. 10.1016/j.neuroimage.2011.06.042. Gold open access

Ozogur-Akyuz, S; Shawe-Taylor, J; Weber, G-W; Ogel, ZB; (2009) Pattern analysis for the prediction of fungal pro-peptide cleavage sites. DISCRETE APPLIED MATHEMATICS , 157 (10) pp. 2388-2394. 10.1016/j.dam.2008.06.043.

Papangelis, A; Metsis, V; Shawe-Taylor, J; Makedon, F; (2010) Sensor placement and coordination via distributed multi-agent cooperative control. ACM International Conference Proceeding Series 10.1145/1839294.1839311.

Parrado-Hernandez, E; Ambroladze, A; Shawe-Taylor, J; Sun, S; (2012) PAC-Bayes Bounds with Data Dependent Priors. JOURNAL OF MACHINE LEARNING RESEARCH , 13 pp. 3507-3531. Gold open access

Parrado-Hernández, E; Gómez-Verdejo, V; Martínez-Ramón, M; Shawe-Taylor, J; Alonso, P; Pujol, J; Menchón, JM; ... Soriano-Mas, C; + view all (2012) Voxel selection in MRI through bagging and conformal analysis: Application to detection of obsessive compulsive disorder. Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012 pp. 49-52. 10.1109/PRNI.2012.30.

Pasupa, K; Hussain, Z; Shawe-Taylor, J; Willett, P; (2013) Drug screening with elastic-net multiple kernel learning. 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013 10.1109/BIBE.2013.6701529.

Pavisic, IM; Firth, NF; Parsons, S; Martinez Rego, D; Shakespeare, TJ; Yong, KXX; Slattery, CF; ... Primativo, S; + view all (2017) Eyetracking Metrics in Young Onset Alzheimer’s Disease: A Window into Cognitive Visual Functions. Frontiers in Neurology , 8 , Article 377. 10.3389/fneur.2017.00377. Green open access
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Pica, G; Pisanski, T; Shawe-Taylor, J; (1985) Generalised Chromatic Numbers of some Graphs II. Rivista di Matematica della Universit? di Parma , 11 (4) pp. 375-379.

Pignon, D; Parmiter, P; Slack, J; Hands, M; Hall, T; Daalen, M; Shawe-Taylor, J; (1996) Sigmoid Neural Transfer Function Realised by Percolation. Optics Letters , 21 (3) pp. 222-224.

Pisanski, T; Shawe-Taylor, J; (2000) Characterizing Graph Drawing with Eigenvectors. Journal of Chemical Information and Computer Sciences , 40 (3) pp. 567-571.

Pisanski, T; Shawe-Taylor, J; (1981) Search for minimal trivalent cycle permutation graphs with girth nine. Discrete Mathematics , 36 (1) pp. 113-115.

Pisanski, T; Shawe-Taylor, J; Mohar, B; (1983) 1-factorisation of the Composition of Regular Graphs. Publications de l'Institut Math?matique , 33 (47) pp. 193-196.

Pisanski, T; Shawe-Taylor, J; Vrabec, J; (1983) Edge-colorability of graph bundles. J. Comb. Theory, Ser. B , 35 (1) pp. 12-19.

Rondina, J; Hahn, T; de Oliveira, L; Marquand, A; Dresler, T; Leitner, T; Fallgatter, A; ... Mourao-Miranda, J; + view all (2014) SCoRS - a method based on stability for feature selection and mapping in neuroimaging. IEEE Trans Med Imaging , 33 (1) pp. 85-98. 10.1109/TMI.2013.2281398. Green open access
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Rosa, MJ; Portugal, L; Hahn, T; Fallgatter, AJ; Garrido, MI; Shawe-Taylor, J; Mourao-Miranda, J; (2015) Sparse network-based models for patient classification using fMRI. Neuroimage , 105 493 - 506. 10.1016/j.neuroimage.2014.11.021. Green open access
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Rousu, J; Agranoff, DD; Sodeinde, O; Shawe-Taylor, J; Fernandez-Reyes, D; (2013) Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria. PLoS Computational Biology , 9 (4) , Article e1003018. 10.1371/journal.pcbi.1003018. Green open access
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Rousu, J; Saunders, C; Szedmak, S; Shawe-Taylor, J; (2006) Learning Hierarchical Multi-Category Text Classification Models. Journal of Machine Learning Research , 7 pp. 1601-1626. Gold open access

Rousu, J; Saunders, C; Szedmák, S; Shawe-Taylor, J; (2006) Kernel-Based Learning of Hierarchical Multilabel Classification Models. Journal of Machine Learning Research , 7 pp. 1601-1626. Gold open access

Rousu, J; Shawe-Taylor, J; (2005) Efficient Computation of Gapped Substring Kernels on Large Alphabets. Journal of Machine Learning Research , 6 pp. 1323-1344. Gold open access

Saunders, C; Hardoon, DR; Shawe-Taylor, J; Widmer, G; (2008) Using string kernels to identify famous performers from their playing style. INTELLIGENT DATA ANALYSIS , 12 (4) pp. 425-440.

Schölkopf, B; Platt, JC; Shawe-Taylor, J; Smola, AJ; Williamson, RC; (2001) Estimating the Support of a High-Dimensional Distribution. Neural Computation , 13 (7) pp. 1443-1471.

Seldin, Y; Auer, P; Laviolette, F; Shawe-Taylor, J; Ortner, R; (2011) PAC-Bayesian analysis of contextual bandits. Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Seldin, Y; Cesa-Bianchi, N; Auer, P; Laviolette, F; Shawe-Taylor, J; (2012) PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. ICML On-line Trading of Exploration and Exploitation , 26 pp. 98-111.

Seldin, Y; Cesa-Bianchi, N; Auer, P; Laviolette, F; Shawe-Taylor, J; (2011) PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits. CoRR , abs/11

Seldin, Y; Cesa-Bianchi, N; Laviolette, F; Auer, P; Shawe-Taylor, J; Peters, J; (2011) PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off. CoRR , abs/11

Seldin, Y; Laviolette, F; Cesa-Bianchi, N; Shawe-Taylor, J; Auer, P; (2012) PAC-Bayesian Inequalities for Martingales. IEEE TRANSACTIONS ON INFORMATION THEORY , 58 (12) pp. 7086-7093. 10.1109/TIT.2012.2211334.

Seldin, Y; Laviolette, F; Cesa-Bianchi, N; Shawe-Taylor, J; Auer, P; (2012) PAC-Bayesian Inequalities for Martingales. IEEE Trans. Information Theory , 58 (12) pp. 7086-7093.

Seldin, Y; Laviolette, F; Shawe-Taylor, J; Peters, J; Auer, P; (2011) PAC-Bayesian Analysis of Martingales and Multiarmed Bandits. CoRR , abs/11

Sewell, M; Shawe-Taylor, J; (2012) Forecasting foreign exchange rates using kernel methods. EXPERT SYSTEMS WITH APPLICATIONS , 39 (9) pp. 7652-7662. 10.1016/j.eswa.2012.01.026.

Sewell, M; Shawe-Taylor, J; (2012) Forecasting foreign exchange rates using kernel methods. Expert Systems with Applications , 39 (9) pp. 7652-7662. 10.1016/j.eswa.2012.01.026.

Shawe- Taylor, J; Parrado-Hernández, E; Ambroladze, A; (2010) Data dependent priors in PAC-Bayes bounds. Proceedings of COMPSTAT 2010 - 19th International Conference on Computational Statistics, Keynote, Invited and Contributed Papers pp. 231-240. 10.1007/978-3-7908-2604-3-21.

Shawe-Taylor, J; (2009) Machine Learning for Complex Predictions. COMMUNICATIONS OF THE ACM , 52 (11) p. 96. 10.1145/1592761.1592782.

Shawe-Taylor, J; (2009) Machine Learning for Complex Predictions. COMMUNICATIONS OF THE ACM , 52 (11) p. 96. 10.1145/1592761.1592782.

Shawe-Taylor, J; (2001) Neural Network Learning: Theoretical Foundation. AI Magazine , 22 (2) pp. 99-100.

Shawe-Taylor, J; (1998) Classification Accuracy Based on Observed Margin. Algorithmica , 22 (1/2) pp. 157-172.

Shawe-Taylor, J; (1998) Special Issue of DAM on the Vapnik-chervonenkis Dimension. Discrete Applied Mathematics , 86 (1) pp. 1-2.

Shawe-Taylor, J; (1996) Fast String Matching in Stationary Ergodic Sources. Combinatorics, Probability & Computing , 5 pp. 415-427.

Shawe-Taylor, J; (1995) Sample Sizes for Threshold Networks with Equivalences. Inf. Comput. , 118 (1) pp. 65-72.

Shawe-Taylor, J; (1994) Coverings of complete bipartite graphs and associated structures. Discrete Mathematics , 134 (1-3) pp. 151-160.

Shawe-Taylor, J; (1993) Symmetries and Discriminability in Feedforward Network Architectures. IEEE Transactions on Neural Networks , 4 (5) pp. 816-826.

Shawe-Taylor, J; (1992) Proportion of primes generated by strong prime methods. Electronics Letters , 28 (2) pp. 135-136.

Shawe-Taylor, J; (1987) Automorphism Groups of Primitive Distance-bitransitive Graphs are Almost Simple. European Journal of Combinatorics , 8 (2) pp. 187-197.

Shawe-Taylor, J; (1987) Information and its Relation to Formalisms for the Complexities of the Real World. Journal of Information Technology. , 2 (3) pp. 151-155.

Shawe-Taylor, J; (1986) Generating Strong Primes. Electronics Letters , 22 (16) pp. 875-877.

Shawe-Taylor, J; Anthony, M; (1991) Sample Sizes for Multiple Output Threshold Networks. Network , 2 (1) pp. 107-117.

Shawe-Taylor, J; Anthony, M; Biggs, N; (1993) Bounding Sample Size with the Vapnik-Chervonenkis Dimension. Discrete Applied Mathematics , 42 (1) pp. 65-73.

Shawe-Taylor, J; Anthony, M; Kern, W; (1992) Classes of feedforward neural networks and their circuit complexity. Neural Networks , 5 (6) pp. 971-977.

Shawe-Taylor, J; Bartlett, PL; Williamson, RC; Anthony, M; (1998) Structural Risk Minimization Over Data-Dependent Hierarchies. IEEE Trans. Information Theory , 44 (5) pp. 1926-1940.

Shawe-Taylor, J; Cohen, DA; (1990) Linear programming algorithm for neural networks. Neural Networks , 3 (5) pp. 575-582.

Shawe-Taylor, J; Cristianini, N; (2002) On the generalization of soft margin algorithms. IEEE Trans. Information Theory , 48 (10) pp. 2721-2735. Green open access
file

Shawe-Taylor, J; De Bie, T; Cristianini, N; (2006) Data mining, data fusion and information management. IEE Proceedings: Intelligent Transport Systems , 153 (3) 10.1049/ip-its:20060006.

Shawe-Taylor, J; Hardoon, DR; (2009) PAC-Bayes Analysis Of Maximum Entropy Classification. AISTATS , 5 pp. 480-487.

Shawe-Taylor, J; Howker, K; Burge, P; (1999) Detection of fraud in mobile telecommunications. Information Security Technical Report , 4 (1) pp. 16-28.

Shawe-Taylor, J; Jeavons, P; Daalen, M; (1991) Probabilistic Bit Stream Neural Chip: Theory. Connection Science , 3 (3) pp. 317-328.

Shawe-Taylor, J; Pisanski, T; (1994) Homeomorphism of 2-Complexes is Graph Isomorphism Complete. SIAM J. Comput. , 23 (1) pp. 120-132.

Shawe-Taylor, J; Pisanski, T; (1982) Cycle Permutation Graphs with Large Girth. Glasnik Matemati?ki , 17 (2) pp. 233-236.

Shawe-Taylor, J; Sun, S; (2011) A review of optimization methodologies in support vector machines. NEUROCOMPUTING , 74 (17) pp. 3609-3618. 10.1016/j.neucom.2011.06.026.

Shawe-Taylor, J; Williams, CKI; Cristianini, N; Kandola, JS; (2005) On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA. IEEE Trans. Information Theory , 51 (7) pp. 2510-2522. Green open access
file

Shawe-Taylor, J; Zerovnik, J; (1995) Analysis of the Mean Field Annealing Algorithm for Graph Colouring. Journal of Artificial Neural Networks , 2 (4) pp. 329-340.

Shen, Y; Archambeau, C; Cornford, D; Opper, M; Shawe-Taylor, J; Barillec, R; (2010) A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY , 61 (1) pp. 51-59. 10.1007/s11265-008-0299-y.

Shen, Y; Archambeau, C; Cornford, D; Opper, M; Shawe-Taylor, J; Barillec, R; (2010) A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY , 61 (1) pp. 51-59. 10.1007/s11265-008-0299-y.

Sun, S; Shawe-Taylor, J; (2010) Sparse Semi-supervised Learning Using Conjugate Functions. Journal of Machine Learning Research , 11 2423 - 2455. Green open access
file

Sun, S; Shawe-Taylor, J; Mao, L; (2017) PAC-Bayes analysis of multi-view learning. Information Fusion , 35 pp. 117-131. 10.1016/j.inffus.2016.09.008. Green open access
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Sun, Y; Best, K; Cinelli, M; Heather, JM; Reich-Zeliger, S; Shifrut, E; Friedman, N; ... Chain, B; + view all (2017) Specificity, Privacy, and Degeneracy in the CD4 T Cell Receptor Repertoire Following Immunization. Front Immunol , 8 , Article 430. 10.3389/fimmu.2017.00430. Green open access
file

Szedmak, S; Shawe-Taylor, J; (2007) Synthesis of maximum margin and multiview learning using unlabeled data. NEUROCOMPUTING , 70 (7-9) pp. 1254-1264. 10.1016/j.neucom.2006.11.012.

Thomas, N; Best, K; Cinelli, M; Reich-Zeliger, S; Gal, H; Shifrut, E; Madi, A; ... Chain, B; + view all (2014) Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinformatics , 30 (22) 3181 - 3188. 10.1093/bioinformatics/btu523. Green open access
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Thomas, N; Heather, J; Ndifon, W; Shawe-Taylor, J; Chain, B; (2013) Decombinator: a tool for fast, efficient gene assignment in T-cell receptor sequences using a finite state machine. BIOINFORMATICS , 29 (5) pp. 542-550. 10.1093/bioinformatics/btt004.

Thomas, N; Heather, J; Pollara, G; Simpson, N; Matjeka, T; Shawe-Taylor, J; Noursadeghi, M; (2013) The immune system as a biomonitor: explorations in innate and adaptive immunity. INTERFACE FOCUS , 3 (2) 10.1098/rsfs.2012.0099.

Thomas, N; Matejovicova, L; Srikusalanukul, W; Shawe-Taylor, J; Chain, B; (2012) Directional migration of recirculating lymphocytes through lymph nodes via random walks. PLoS One , 7 (9) , Article e45262. 10.1371/journal.pone.0045262. Green open access
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Tsampouka, P; Shawe-Taylor, J; (2007) Approximate maximum margin algorithms with rules controlled by the number of mistakes. ACM International Conference Proceeding Series , 227 pp. 903-910. 10.1145/1273496.1273610.

Uurtio, V; Monteiro, JM; Kandola, J; Shawe-Taylor, J; Fernandez-Reyes, D; Rousu, J; (2018) A Tutorial on Canonical Correlation Methods. ACM Computing Surveys (CSUR) , 50 (6) , Article 95. 10.1145/3136624. Green open access
file

VANDAALEN, M; ZHAO, J; SHAWETAYLOR, J; (1994) REAL-TIME OUTPUT DERIVATIVES FOR ON CHIP LEARNING USING DIGITAL STOCHASTIC BIT STREAM NEURONS. ELECTRONICS LETTERS , 30 (21) pp. 1775-1777. 10.1049/el:19941233.

Wang, Z; Shah, AD; Tate, AR; Denaxas, S; Shawe-Taylor, J; Hemingway, H; (2012) Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning. PLOS One , 7 (1) , Article e30412. 10.1371/journal.pone.0030412. Green open access
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Wang, Z; Shawe-Taylor, J; (2010) A kernel regression framework for SMT. Machine Translation , 24 (2) pp. 87-102. 10.1007/s10590-010-9079-0.

Wang, Z; Shawe-Taylor, J; Shah, A; (2010) Semi-Supervised Feature Learning from Clinical Text. 2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE pp. 462-466.

Wood, J; Shawe-Taylor, J; (1996) Representation Theory and Invariant Neural Networks. Discrete Applied Mathematics , 69 (1-2) pp. 33-60.

Wood, J; Shawe-Taylor, J; (1996) A unifying framework for invariant pattern recognition. Pattern Recognition Letters , 17 (14) pp. 1415-1422.

Zhao, J; Shawe-Taylor, J; Daalen, MV; (1996) Learning in Stochastic Bit Stream Neural Networks. Neural Networks , 9 (6) pp. 991-998.

Özögür-Akyüz, S; Hussain, Z; Shawe-Taylor, J; (2010) Prediction with the SVM Using Test Point Margins. pp. 147-158.

Book

Anthony, M; Shawe-Taylor, J; (1994) First European Conference on Computational Learning Theory (EuroCOLT'93). [Book]. The Institute of Mathematics and Its Applications Conference Series: Vol.23. Oxford University Press

Baumgartner, E; Baumgartner, W; Borstner, B; Potrc, M; Shawe-Taylor, J; Valentine, E; (1996) Handbook of Phenomenology and Cognitive Science. [Book]. Dettelbach, R"oll

Cristianini, N; Shawe-Taylor, J; (2010) An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press

Cristianini, N; Shawe-Taylor, J; (2000) An introduction to Support Vector Machines. [Book]. Cambridge University Press

Saunders, CJ; Gunn, SR; Grobelnik, M; Shawe-Taylor, J; Eds, S; (2006) Subspace, Latent Structure and Feature Selection techniques. [Book].

Shawe-Taylor, J; (2001) Review of "Anthony, Martin; Bartlett, Peter L., Neural Network Learning: Theoretical Foundations, Cambridge: Cambridge University Press". [Book]. Cambridge University Press

Shawe-Taylor, J; (1995) Consciousness at the Crossroads of Philosophy and Cognitive Science, Special issue of Journal of Consciousness Studies. [Book]. Thorverton: Imprint Academic

Shawe-Taylor, J; (1989) Review of "Cryptography - An Introduction to Computer Security", by Seberry and Peiprzek. [Book]. Prentice Hall advances in computer science series: Vol.12. Prentice Hall, Sydney

Shawe-Taylor, J; Singer, Y; (2004) Learning Theory, Proceedings of 17th Annual Conference on Learning Theory, COLT 2004. [Book]. Lecture Notes in Computer Science (LNCS, LNAI): Vol.3120. Springer

Book chapter

Ambroladze, A; Shawe-Taylor, J; (2003) When Is Small Beautiful? In: Schölkopf, B and Warmuth, MK, (eds.) Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings. (pp. 729-730). Springer

Anthony, M; Biggs, N; Shawe-Taylor, J; (1990) The Learnability of Formal Concepts. In: Fulk, MA and Case, J, (eds.) Proceedings of the Third Annual Workshop on Computational Learning Theory, COLT 1990, University of Rochester, Rochester, NY, USA, August 6-8, 1990. (pp. 246-257). Morgan Kaufmann

Anthony, M; Brightwell, GR; Cohen, DA; Shawe-Taylor, J; (1992) On Exact Specification by Examples. In: Haussler, D, (ed.) Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, COLT 1992, Pittsburgh, PA, USA, July 27-29, 1992. (pp. 311-318). ACM

Anthony, M; Shawe-Taylor, J; (1994) Valid Generalisation of Functions from Close Approximations on a Sample. In: UNSPECIFIED Oxford University Press

Anthony, M; Shawe-Taylor, J; (1993) Bounds On the Complexity of Testing and Loading Neurons. In: UNSPECIFIED (pp. 756-759). Springer Verlag

Bartlett, P; Shawe-Taylor, J; (1998) Generalization Performance of Support Vector Machines and Other Pattern Classifiers. In: UNSPECIFIED MIT Press, Cambridge, USA

Baxter, J; Shawe-Taylor, J; (1996) Learning to Compress Ergodic Sources. In: Storer, JA and Cohn, M, (eds.) Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31 - April 3, 1996. (p. 423). IEEE Computer Society

Biggs, N; Shawe-Taylor, J; (1984) Rotations and Graphs with Large Girth. In: UNSPECIFIED Pitman Advanced Publ. Program

Burge, P; Daalen, M; Rising, B; Shawe-Taylor, J; (1999) Stochastic Bit-stream Neural Networks. In: UNSPECIFIED (pp. 337-352). MIT Press

Burge, P; Shawe-Taylor, J; (1997) Detecting Cellular Fraud Using Adaptive Prototypes. In: UNSPECIFIED (pp. 9-13). AAAI Press

Burge, P; Shawe-Taylor, J; (1996) Frameworks For Fraud Detection In Mobile Telecommunications Networks. In: UNSPECIFIED

Burge, P; Shawe-Taylor, J; Cooke, C; Moreau, Y; Preneel, B; Stoermann, C; (1997) Advanced Fraud Detection Techniques for Mobile Telephone Systems. In: UNSPECIFIED (pp. 91-96). IEE

Burge, P; Shawe-Taylor, J; Moreau, Y; Verrelst, H; Stoermann, C; Gosset, P; (1997) BRUTUS - A Hybrid Detection Tool. In: UNSPECIFIED

Cohen, D; Mannion, C; Shawe-Taylor, J; (1988) Towards a Transformational Theory of Feedforward Neural Networks. In: UNSPECIFIED

Cohen, D; Shawe-Taylor, J; (1989) Feedforward Neural Networks: a Tutorial. In: UNSPECIFIED Inst of Physics Pub Inc

Cristianini, N; Campbell, C; Shawe-Taylor, J; (1999) Multiplicative Updatings for Support Vector Learning. In: UNSPECIFIED (pp. 189-194). D-Facto Publications

Cristianini, N; Campbell, C; Shawe-Taylor, J; (1998) Dynamically Adapting Kernels in Support Vector Machines. In: Kearns, MJ and Solla, SA and Cohn, DA, (eds.) Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30 - December 5, 1998]. (pp. 204-210). The MIT Press

Cristianini, N; Shawe-Taylor, J; Elisseeff, A; Kandola, JS; (2001) On Kernel-Target Alignment. In: Dietterich, TG and Becker, S and Ghahramani, Z, (eds.) Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. (pp. 367-373). MIT Press

Cristianini, N; Shawe-Taylor, J; Kandola, JS; (2001) Spectral Kernel Methods for Clustering. In: Dietterich, TG and Becker, S and Ghahramani, Z, (eds.) Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. (pp. 649-655). MIT Press

Cristianini, N; Shawe-Taylor, J; Lodhi, H; (2001) Latent Semantic Kernels. In: Brodley, CE and Danyluk, AP, (eds.) Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001. (pp. 66-73). Morgan Kaufmann

Cristianini, N; Shawe-Taylor, J; Lodhi, H; (2000) Latent Semantic Kernels. In: UNSPECIFIED (pp. 66-73). Morgan Kaufmann

Cristianini, N; Shawe-Taylor, J; Saunders, C; (2007) Kernel Methods: A Paradigm for Pattern Analysis. In: In Camps-Valls, G and Rojo-Alvarez, J and Martinez-Ramon, M, (eds.) Kernel Methods in Bioengineering, Signal and Image Processing. (pp. 1-40). IDEA Group Publishing

Cristianini, N; Shawe-Taylor, J; Sykacek, P; (1998) Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space. In: Shavlik, JW, (ed.) Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconsin, USA, July 24-27, 1998. (pp. 109-117). Morgan Kaufmann

Crossland, W; Hall, T; Shawe-Taylor, J; Daalen, M; (1994) Optical implementation of a stochastic neural system. In: UNSPECIFIED (pp. 395-398). IOP Publishing

Daalen, M; Jeavons, P; Shawe-Taylor, J; (1993) A stochastic neural architecture that exploits dynamically reconfigurable FPGAs. In: UNSPECIFIED (pp. 202-211). IEEE Computer Society Press

Daalen, M; Jeavons, P; Shawe-Taylor, J; (1991) Probabilistic Bit Stream Neural Chip: Implementation. In: UNSPECIFIED (pp. 285-294). New York: Plenum

Domingo, C; Shawe-Taylor, J; (1995) The Complexity of Learning Minor Closed Graph Classes. In: Jantke, KP and Shinohara, T and Zeugmann, T, (eds.) Algorithmic Learning Theory, 6th International Conference, ALT '95, Fukuoka, Japan, October 18-20, 1995, Proceedings. (pp. 249-260). Springer

Everingham, M; Zisserman, A; Williams, CKI; Gool, LJV; Allan, M; Bishop, CM; Chapelle, O; ... Zhang, J; + view all (2005) The 2005 PASCAL Visual Object Classes Challenge. In: Candela, JQ and Dagan, I and Magnini, B and d'Alché-Buc, F, (eds.) Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers. (pp. 117-176). Springer

Fowler, PW; Pisanski, T; Shawe-Taylor, J; (1994) Molecular Graph Eigenvectors for Molecular Coordinates. In: Tamassia, R and Tollis, IG, (eds.) Graph Drawing, DIMACS International Workshop, GD '94, Princeton, New Jersey, USA, October 10-12, 1994, Proceedings. (pp. 282-285). Springer

Graepel, T; Herbrich, R; (2004) Semidefinite programming by perceptron learning. In: Thrun, S and Saul, K and Scholkopf, B, (eds.) UNSPECIFIED (pp. 457-464). M I T PRESS

Graepel, T; Herbrich, R; Shawe-Taylor, J; (2000) Generalisation Error Bounds for Sparse Linear Classifiers. In: Cesa-Bianchi, N and Goldman, SA, (eds.) Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28 - July 1, 2000, Palo Alto, California, USA. (pp. 298-303). Morgan Kaufmann

Graepel, T; Herbrich, R; Shawe-Taylor, J; (2000) Sparsity vs. Large Margins for Linear Classifiers: A Small Sample Size Study. In: UNSPECIFIED (pp. 304-308). Morgan Kaufmann

Guo, Y; Bartlett, PL; Shawe-Taylor, J; Williamson, RC; (1999) Covering Numbers for Support Vector Machines. In: Ben-David, S and Long, PM, (eds.) Proceedings of the Twelfth Annual Conference on Computational Learning Theory, COLT 1999, Santa Cruz, CA, USA, July 7-9, 1999. (pp. 267-277). ACM

Joachims, T; Cristianini, N; Shawe-Taylor, J; (2001) Composite Kernels for Hypertext Categorisation. In: Brodley, CE and Danyluk, AP, (eds.) Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001. (pp. 250-257). Morgan Kaufmann

Kandola, J; Graepel, T; Shawe-Taylor, J; (2003) Reducing kernel matrix diagonal dominance using semi-definite programming. In: Scholkopf, B and Warmuth, MK, (eds.) UNSPECIFIED (pp. 288-302). SPRINGER-VERLAG BERLIN

Kandola, J; Shawe-Taylor, J; (2003) Refining Kernels for Regression and Uneven Classification Problems. In: UNSPECIFIED Springer-Verlag, Berlin Heidelberg

Kandola, JS; Shawe-Taylor, J; Cristianini, N; (2002) Learning Semantic Similarity. In: Becker, S and Thrun, S and Obermayer, K, (eds.) Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. (pp. 657-664). MIT Press

Karakoulas, G; Shawe-Taylor, J; (2000) Towards a strategy for boosting regressors. In: UNSPECIFIED (pp. 247-258). MIT Press

Karakoulas, GI; Shawe-Taylor, J; (1998) Optimizing Classifers for Imbalanced Training Sets. In: Kearns, MJ and Solla, SA and Cohn, DA, (eds.) Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30 - December 5, 1998]. (pp. 253-259). The MIT Press

Kim, J; Shawe-Taylor, J; (1993) Fast Expected Two Dimensional Pattern Matching. In: UNSPECIFIED (pp. 77-92). Carleton University Press, International Informatics Series

Kim, JY; Shawe-Taylor, J; (1992) Fast Multiple Keyword Searching. In: Apostolico, A and Crochemore, M and Galil, Z and Manber, U, (eds.) Combinatorial Pattern Matching, Third Annual Symposium, CPM 92, Tucson, Arizona, USA, April 29 - May 1, 1992, Proceedings. (pp. 41-51). Springer

Li, Y; Zaragoza, H; Herbrich, R; Shawe-Taylor, J; Kandola, JS; (2002) The Perceptron Algorithm with Uneven Margins. In: Sammut, C and Hoffmann, AG, (eds.) Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), University of New South Wales, Sydney, Australia, July 8-12, 2002. (pp. 379-386). Morgan Kaufmann

Lodhi, H; Karakoulas, GI; Shawe-Taylor, J; (2000) Boosting the Margin Distribution. In: Leung, K-S and Chan, L-W and Meng, H, (eds.) Intelligent Data Engineering and Automated Learning - IDEAL 2000, Data Mining, Financial Engineering, and Intelligent Agents, Second International Conference, Shatin, N.T. Hong Kong, China, December 13-15, 2000, Proceedings. (pp. 54-59). Springer

Lodhi, H; Shawe-Taylor, J; Cristianini, N; Watkins, CJCH; (2000) Text Classification using String Kernels. In: Leen, TK and Dietterich, TG and Tresp, V, (eds.) Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA. (pp. 563-569). MIT Press

Marchand, M; Shah, M; Shawe-Taylor, J; Sokolova, M; (2003) The Set Covering Machine with Data-Dependent Half-Spaces. In: Fawcett, T and Mishra, N, (eds.) Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA. (pp. 520-527). AAAI Press

Marchand, M; Shawe-Taylor, J; (2001) Learning with the Set Covering Machine. In: Brodley, CE and Danyluk, AP, (eds.) Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001. (pp. 345-352). Morgan Kaufmann

Meng, H; Shawe-Taylor, J; Szedmák, S; Farquhar, JDR; (2004) Support Vector Machine to Synthesise Kernels. In: Winkler, J and Niranjan, M and Lawrence, ND, (eds.) Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures. (pp. 242-255). Springer

Pisanski, T; Shawe-Taylor, J; (1981) Cycle Permutation Graphs with Large Girth. In: UNSPECIFIED Cambridge University Press

Platt, JC; Cristianini, N; Shawe-Taylor, J; (1999) Large Margin DAGs for Multiclass Classification. In: Solla, SA and Leen, TK and Müller, K-R, (eds.) Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]. (pp. 547-553). The MIT Press

Rising, B; Daalen, MV; Burge, P; Shawe-Taylor, J; (1997) Parallel Graph colouring using FPGAs. In: Luk, W and Cheung, PYK and Glesner, M, (eds.) Field-Programmable Logic and Applications, 7th International Workshop, FPL '97, London, UK, September 1-3, 1997, Proceedings. (pp. 121-130). Springer

Rising, B; Daalen, MV; Shawe-Taylor, J; Burge, P; Zerovnik, J; (1998) A Neural Accelerator for Graph Colouring Based on an Edge Adding Technique. In: Heiss, M, (ed.) Proceedings of the International ICSC / IFAC Symposium on Neural Computation (NC 1998), September 23-15, 1998, Vienna, Austria. (pp. 652-656). ICSC Academic Press, International Computer Science Conventions, Canada / Switzerland

Rising, B; Shawe-Taylor, J; Zerovnik, J; (2000) Graph Colouring by Maximal Evidence Edge Adding. In: UNSPECIFIED Springer-Verlag

Rising, B; Shawe-Taylor, J; Zerovnik, J; (2000) Graph Colouring by Maximal Evidence Edge Adding. In: Burke, EK and Erben, W, (eds.) Practice and Theory of Automated Timetabling III, Third International Conference, PATAT 2000, Konstanz, Germany, August 16-18, 2000, Selected Papers. (pp. 294-308). Springer

Rychetsky, M; Shawe-Taylor, J; Glesner, M; (2000) Direct Bayes Point Machines. In: Langley, P, (ed.) Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000. (pp. 815-822). Morgan Kaufmann

SHAWE-TAYLOR, J; Fortuna, B; Cristianini, N; (2007) A Kernel Canonical Correlation Analysis for Learning the Semantics of Text. In: Rojo-Alvarez, G and In Camps-Valls, G and Rojo-Alvarez, J and Martinez-Ramon, M, (eds.) Kernel Methods in Bioengineering, Signal and Image Processing. (pp. 263-282).

Saunders, C; Shawe-Taylor, J; Vinokourov, A; (2002) String Kernels, Fisher Kernels and Finite State Automata. In: Becker, S and Thrun, S and Obermayer, K, (eds.) Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. (pp. 633-640). MIT Press

Saunders, C; Tschach, H; Shawe-Taylor, J; (2002) Syllables and other String Kernel Extensions. In: Sammut, C and Hoffmann, AG, (eds.) Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), University of New South Wales, Sydney, Australia, July 8-12, 2002. (pp. 530-537). Morgan Kaufmann

Scholkopf, B; Williamson, R; Smola, A; Shawe-Taylor, J; (2000) SV Estimation of a Distribution's Support. In: UNSPECIFIED (pp. 582-588). MIT Press

Shawe-Taylor, J; (2001) Optimisation in Machine Learning: Some Recent Developments and Perspectives. In: UNSPECIFIED (pp. 25-35).

Shawe-Taylor, J; (1999) Introducing the Special Issue of Machine Learning Selected from Papers Presented at the 1997 Conference on Computational Learning Theory, COLT'97. In: UNSPECIFIED (pp. 191-192).

Shawe-Taylor, J; (1999) Theoretical analysis of real-valued function classes, Guest editorial. In: UNSPECIFIED (pp. 1-2). Elsevier Science

Shawe-Taylor, J; (1998) Preface to the Special issue on the Vapnik-Chervonenkis dimension. In: UNSPECIFIED (pp. 1-2). Elsevier Science

Shawe-Taylor, J; (1997) Confidence Estimates of Classification Accuracy on New Examples. In: Ben-David, S, (ed.) Computational Learning Theory, Third European Conference, EuroCOLT '97, Jerusalem, Israel, March 17-19, 1997, Proceedings. (pp. 260-271). Springer

Shawe-Taylor, J; (1996) Continuous Models of Computation. In: UNSPECIFIED Josef H R?ll, Dettelbach, Germany

Shawe-Taylor, J; (1996) Mathematical Models of Learning and Connectionism. In: UNSPECIFIED Dettelbach, R?ll

Shawe-Taylor, J; (1995) Generalisation Analysis for Classes of Continuous Neural Networks. In: UNSPECIFIED (pp. 2944-2948). IEEE Neural Networks Council

Shawe-Taylor, J; (1995) Sample Sizes for Sigmoidal Neural Networks. In: Maass, W, (ed.) Proceedings of the Eigth Annual Conference on Computational Learning Theory, COLT 1995, Santa Cruz, California, USA, July 5-8, 1995. (pp. 258-264). ACM

Shawe-Taylor, J; (1994) Introducing invariance: a principled approach to weight sharing. In: UNSPECIFIED (pp. 345-349).

Shawe-Taylor, J; (1991) Threshold Network Learning in the Presence of Equivalences. In: Moody, JE and Hanson, SJ and Lippmann, R, (eds.) Advances in Neural Information Processing Systems 4, [NIPS Conference, Denver, Colorado, USA, December 2-5, 1991]. (pp. 879-886). Morgan Kaufmann

Shawe-Taylor, J; (1989) Building Symmetries into Feedforward Networks. In: UNSPECIFIED (pp. 158-162). Inspec/Iee

Shawe-Taylor, J; Bartlett, PL; Williamson, RC; Anthony, M; (1996) A Framework for Structural Risk Minimisation. In: Blum, A and Kearns, MJ, (eds.) Proceedings of the Ninth Annual Conference on Computational Learning Theory, COLT 1996, Desenzano del Garda, Italy, June 28-July 1, 1996. (pp. 68-76). ACM

Shawe-Taylor, J; Cristianini, N; (2003) Estimating the moments of a random vector with applications. In: UNSPECIFIED

Shawe-Taylor, J; Cristianini, N; (2000) Margin Distribution and Soft Margin. In: UNSPECIFIED (pp. 349-358). MIT Press

Shawe-Taylor, J; Cristianini, N; (1999) Further Results on the Margin Distribution. In: Ben-David, S and Long, PM, (eds.) Proceedings of the Twelfth Annual Conference on Computational Learning Theory, COLT 1999, Santa Cruz, CA, USA, July 7-9, 1999. (pp. 278-285). ACM

Shawe-Taylor, J; Cristianini, N; (1999) Generalization Performance of Classifiers in Terms of Observed Covering Numbers. In: Fischer, P and Simon, HU, (eds.) Computational Learning Theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31, 1999, Proceedings. (pp. 274-284). Springer

Shawe-Taylor, J; Cristianini, N; (1999) Margin Distribution Bounds on Generalization. In: Fischer, P and Simon, HU, (eds.) Computational Learning Theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31, 1999, Proceedings. (pp. 263-273). Springer

Shawe-Taylor, J; Cristianini, N; (1997) Data-Dependent Structural Risk Minimization for Perceptron Decision Trees. In: Jordan, MI and Kearns, MJ and Solla, SA, (eds.) Advances in Neural Information Processing Systems 10, [NIPS Conference, Denver, Colorado, USA, 1997]. (pp. 336-342). The MIT Press

Shawe-Taylor, J; Cristianini, N; Kandola, JS; (2001) On the Concentration of Spectral Properties. In: Dietterich, TG and Becker, S and Ghahramani, Z, (eds.) Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. (pp. 511-517). MIT Press

Shawe-Taylor, J; Shawe-Taylor, M; (1995) Consciousness as a Linear Phenomenon. In: UNSPECIFIED (pp. 32-38). Thorverton: Imprint Academic

Shawe-Taylor, J; Williams, CKI; (2002) The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum. In: Becker, S and Thrun, S and Obermayer, K, (eds.) Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. (pp. 367-374). MIT Press

Shawe-Taylor, J; Williams, CKI; Cristianini, N; Kandola, JS; (2002) On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. In: Cesa-Bianchi, N and Numao, M and Reischuk, R, (eds.) Algorithmic Learning Theory, 13th International Conference, ALT 2002, Lübeck, Germany, November 24-26, 2002, Proceedings. (pp. 23-40). Springer

Shawe-Taylor, J; Williamson, RC; (1997) A PAC Analysis of a Bayesian Estimator. In: Freund, Y and Schapire, RE, (eds.) Proceedings of the Tenth Annual Conference on Computational Learning Theory, COLT 1997, Nashville, Tennessee, USA, July 6-9, 1997. (pp. 2-9). ACM

Shawe-Taylor, J; Zerovnik, J; (2001) Ants and graph coloring. In: UNSPECIFIED (pp. 276-279). Springer-Verlag

Shawe-Taylor, J; Zerovnik, J; (1992) Boltzmann machines with finite alphabet. In: UNSPECIFIED (pp. 391-394). Elsevier Science and Technology Books

Shawe-Taylor, J; Zhao, J; (1995) Generalisation of A Class of Continuous Neural Networks. In: Touretzky, DS and Mozer, M and Hasselmo, ME, (eds.) Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995. (pp. 267-273). MIT Press

Smola, AJ; Shawe-Taylor, J; Schölkopf, B; Williamson, RC; (1999) The Entropy Regularization Information Criterion. In: Solla, SA and Leen, TK and Müller, K-R, (eds.) Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]. (pp. 342-348). The MIT Press

Sokolova, M; Marchand, M; Japkowicz, N; Shawe-Taylor, J; (2002) The Decision List Machine. In: Becker, S and Thrun, S and Obermayer, K, (eds.) Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. (pp. 921-928). MIT Press

Vinokourov, A; Shawe-Taylor, J; Cristianini, N; (2002) Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis. In: Becker, S and Thrun, S and Obermayer, K, (eds.) Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. (pp. 1473-1480). MIT Press

Wang, Z; Shawe-Taylor, J; (2009) Kernel Based Machine Translation. In: Goutte, C and Cancedda, N and Dyteman, M and Foster, G, (eds.) Learning Machine Translation. MIT Press

Wu, D; Bennett, KP; Cristianini, N; Shawe-Taylor, J; (1999) Large Margin Trees for Induction and Transduction. In: Bratko, I and Dzeroski, S, (eds.) Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999. (pp. 474-483). Morgan Kaufmann

Zhao, J; Shawe-Taylor, J; (1995) Stochastic Connection Neural Networks. In: UNSPECIFIED (pp. 35-39). IEE Conference Publication 409

Zhao, J; Shawe-Taylor, J; (1994) Neural Network Optimization for Good Generalization Performance. In: UNSPECIFIED (pp. 561-564). Springer-Verlag

Proceedings paper

(2011) Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain. In: Shawe-Taylor, J and Zemel, RS and Bartlett, PL and Pereira, FCN and Weinberger, KQ, (eds.)

(2010) Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada. In: Lafferty, JD and Williams, CKI and Shawe-Taylor, J and Zemel, RS and Culotta, A, (eds.) Curran Associates, Inc.

(2009) Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part II. In: Buntine, WL and Grobelnik, M and Mladenic, D and Shawe-Taylor, J, (eds.) Springer

(2007) Advances in Intelligent Data Analysis VII, 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, Proceedings. In: Berthold, MR and Shawe-Taylor, J and Lavrac, N, (eds.) Springer

(2006) Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers. In: Saunders, C and Grobelnik, M and Gunn, SR and Shawe-Taylor, J, (eds.) Springer

(2004) Learning Theory, 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings. In: Shawe-Taylor, J and Singer, Y, (eds.) Springer

Altun, H; Shawe-Taylor, J; Polat, G; (2007) New feature selection frameworks in emotion recognition to evaluate the informative power of speech related features. In: (Proceedings) 9th International Symposium on Signal Processing and its Applications. (pp. 564-+). IEEE

Altun, H; Shawe-Taylor, J; Polat, G; (2007) New feature selection frameworks in emotion recognition to evaluate the informative power of speech related features. In: (pp. pp. 1-4). IEEE

Ambroladze, A; Parrado-Hernández, E; Shawe-Taylor, J; (2007) Tighter PAC-Bayes bounds. In: (pp. pp. 9-16).

Ambroladze, A; Shawe-Taylor, J; (2008) The Ingredients of the Fundamental Theorem of Learning. In: Moor, BD, (ed.) (pp. pp. 1-8). Katholieke Universiteit Leuven: Leuven, Belgium.

Ambroladze, A; Shawe-Taylor, J; (2004) UNSPECIFIED In: (Proceedings) Complexity of pattern classes and Lipschitz property.

Ambroladze, A; Shawe-Taylor, J; (2004) Complexity of Pattern Classes and Lipschitz Property. In: Ben-David, S and Case, J and Maruoka, A, (eds.) (pp. pp. 181-193). Springer

Archambeau, C; Opper, M; Shen, Y; Cornford, D; Shawe-Taylor, J; (2009) Variational inference for diffusion processes. In:

Bennett, KP; Demiriz, A; Shawe-Taylor, J; (2000) A Column Generation Algorithm For Boosting. In: Langley, P, (ed.) (pp. pp. 65-72). Morgan Kaufmann

Cancedda, N; Goutte, C; Renders, J-M; Cesa-Bianchi, N; Conconi, A; Li, Y; Shawe-Taylor, J; ... Gentile, C; + view all (2002) Kernel Methods for Document Filtering. In: Voorhees, EM and Buckland, LP, (eds.) National Institute of Standards and Technology (NIST)

Cristianini, N; Campbell, C; Shawe-Taylor, J; (1999) A multiplicative updating algorithm for training support vector machine. In: (pp. pp. 189-194).

Dhanjal, C; Gunn, S; Shawe-Taylor, J; (2006) UNSPECIFIED In: (Proceedings) Sparse Feature Extraction using Generalised Partial Least Squares. (pp. pp. 27-32).

Diethe, T; Hussain, Z; Hardoon, DR; Shawe-Taylor, J; (2009) Matching Pursuit Kernel Fisher Discriminant Analysis. In: Dyk, DAV and Welling, M, (eds.) (pp. pp. 121-128). JMLR.org

Diethe, T; Shawe-Taylor, J; (2007) Linear Programming Boosting for the Classification of Musical Genre. In: (Proceedings) Neural Information Processing Systems 2007 Workshop: Music, Brain & Cognition.

Diethe, T; Teodoru, G; Furl, N; Shawe-Taylor, J; (2009) Sparse Multiview Methods for Classification of Musical Genre from Magnetoencephalography Recordings. In: Louhivuori, J and Eerola, T and Saarikallio, S and Himberg, T and Eerola, P-S, (eds.) (pp. pp. 79-82). University of Jyväskylä: Jyväskylä, Finland.

Dolia, AN; Bie, TD; Harris, CJ; Shawe-Taylor, J; Titterington, DM; (2006) The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces. In: Fürnkranz, J and Scheffer, T and Spiliopoulou, M, (eds.) (pp. pp. 630-637). Springer

Donini, M; Martinez-Rego, D; Goodson, M; Shawe-Taylor, J; Pontil, M; (2016) Distributed variance regularized Multitask Learning. In: 2016 International Joint Conference on Neural Networks (IJCNN). (pp. pp. 3101-3109). IEEE Green open access
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Donini, M; Monteiro, JM; Pontil, M; Shawe-Taylor, J; Mourao-Miranda, J; (2016) A multimodal multiple kernel learning approach to Alzheimer's disease detection. In: Proceedings of the 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE: Vietri sul Mare, Italy. Green open access
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Dorard, L; Glowacka, D; Shawe-Taylor, J; (2009) GAUSSIAN PROCESS MODELLING OF DEPENDENCIES IN MULTI-ARMED BANDIT PROBLEMS. In: Stirn, LZ and Zerovnik, J and Drobne, S and Lisec, A, (eds.) (Proceedings) 10th International Symposium on Operational Research. (pp. pp. 77-84). SLOVENIAN SOCIETY INFORMATIKA SECTION OPERATIONAL RESEARCH

Dunkin, N; Shawe-Taylor, J; Koiran, P; (1997) A new incremental learning technique. In: Marinaro, M and Tagliaferri, R, (eds.) (pp. pp. 112-118). Springer: New York, US.

Farquhar, JDR; Hardoon, DR; Meng, H; Shawe-Taylor, J; Szedmák, S; (2005) Two view learning: SVM-2K, Theory and Practice. In: (pp. pp. 355-362).

Ferreira, FS; Rosa, MJ; Moutoussis, M; Dolan, R; Shawe-Taylor, J; Ashburner, J; Mourao-Miranda, J; (2018) Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships. In: 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI). IEEE Green open access
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Grünewälder, S; Audibert, JY; Opper, M; Shawe-Taylor, J; (2010) Regret bounds for Gaussian process bandit problems. In: (pp. pp. 273-280). Gold open access

Hardoon, D; Farquhar, JDR; Meng, H; Shawe-Taylor, J; Szedmak, S; (2006) Two view learning: SVM-2K, Theory and Practice. In: Weiss, Y and Scholkof, B and Platt, J, (eds.) (Proceedings) Advances in Neural Information Processing Systems 18. (pp. pp. 355-362). MIT Press: Cambridge, MA.

Hardoon, D; Hussain, Z; Shawe-Taylor, J; (2009) Support Vector Machine Model Selection Using Strangeness. In:

Hardoon, D; Shawe-Taylor, J; (2003) KCCA for different level precision in content-based image retrieval. In: (Proceedings) Third International Workshop on Content-Based Multimedia Indexing.

Hardoon, D; Shawe-Taylor, J; (2003) Signal Extraction for Brain-Computer Interface. In: (Proceedings) NIPS 2003 Workshop on 'Machine Learning Meets the User Interface'.

Hardoon, D; Shawe-Taylor, J; Friman, O; (2004) UNSPECIFIED In: (Proceedings) KCCA for fMRI Analysis.

Hardoon, DR; Mourao-Miranda, J; Brammer, M; Shawe-Taylor, J; (2008) Using image stimuli to drive fMRI analysis. In: Ishikawa, M and Doya, K and Miyamoto, H and Yamakawa, T, (eds.) NEURAL INFORMATION PROCESSING, PART I. (pp. 477 - 486). SPRINGER-VERLAG BERLIN

Hardoon, DR; Mourão-Miranda, J; Brammer, M; Shawe-Taylor, J; (2008) Using image stimuli to drive fMRI analysis. In: (pp. pp. 477-486).

Hardoon, DR; Saunders, C; Szedmák, S; Shawe-Taylor, J; (2006) A Correlation Approach for Automatic Image Annotation. In: Li, X and Zaïane, OR and Li, Z, (eds.) (pp. pp. 681-692). Springer

Hardoon, DR; Shawe-Taylor, J; Ajanki, A; Puolamäki, K; Kaski, S; (2007) Information retrieval by inferring implicit queries from eye movements. In: (pp. pp. 179-186). Gold open access

Henderson, M; Shawe-Taylor, J; Zerovnik, J; (2005) Mixture of Vector Experts. In: Jain, S and Simon, HU and Tomita, E, (eds.) (pp. pp. 386-398). Springer

Herbrich, R; Graepel, T; Shawe-Taylor, J; (2000) Sparsity vs. Large Margins for Linear Classifiers. In: Cesa-Bianchi, N and Goldman, SA, (eds.) (pp. pp. 304-308). Morgan Kaufmann

Hussain, Z; Leung, AP; Pasupa, K; Hardoon, DR; Auer, P; Shawe-Taylor, J; (2010) Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. In: Balcazar, JL and Bonchi, F and Gionis, A and Sebag, M, (eds.) (Proceedings) European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). (pp. pp. 554-569). SPRINGER-VERLAG BERLIN

Hussain, Z; Pasupa, K; Shawe-Taylor, J; (2010) Learning relevant eye movement feature spaces across users. In: Morimoto, CH and Istance, HO and Hyrskykari, A and Ji, Q, (eds.) (pp. pp. 181-185). ACM

Hussain, Z; Shawe-Taylor, J; (2009) Theory of matching pursuit. In: (pp. pp. 721-728).

Hussain, Z; Shawe-Taylor, J; (2008) Using generalization error bounds to train the set covering machine. In: Ishikawa, M and Doya, K and Miyamoto, H and Yamakawa, T, (eds.) NEURAL INFORMATION PROCESSING, PART I. (pp. 258 - 268). SPRINGER-VERLAG BERLIN

Kempinska, K; Davies, T; Shawe-Taylor, J; (2017) Probabilistic map-matching for low-frequency GPS trajectories. In: Proceedings of GIS Ostrava 2017: Dynamics in GIscience. (pp. pp. 209-221). Springer: Ostrava, Czech Republic. Green open access
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Kempinska, KK; Davies, T; Shawe-Taylor, J; (2016) Probabilistic Map-matching using Particle Filters. In: Proceedings of 24th GIS Research UK (GISRUK 2016) Conference. Greenwich GIS Research Group: London, UK. Green open access
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Kharechko, A; Shawe-Taylor, J; Herbrich, R; Graepel, T; (2004) UNSPECIFIED In: (Proceedings) Text Categorization via Ellipsoid Separation.

Langford, J; Shawe-Taylor, J; (2003) UNSPECIFIED In: (Proceedings) PAC Bayes and Margins. MIT Press

Langford, J; Shawe-Taylor, J; (2002) PAC-Bayes & Margins. In: Becker, S and Thrun, S and Obermayer, K, (eds.) (pp. pp. 423-430). MIT Press

Lehmann, AD; Shawe-Taylor, J; (2006) A probabilistic model for text kernels. In: Cohen, WW and Moore, A, (eds.) (pp. pp. 537-544). ACM

Leskovec, J; Shawe-Taylor, J; (2003) UNSPECIFIED In: (Proceedings) Linear Programming Boosting for Uneven Datasets. (pp. pp. 456-463). AAAI Press

Leskovec, J; Shawe-Taylor, J; (2003) Linear Programming Boosting for Uneven Datasets. In: Fawcett, T and Mishra, N, (eds.) (pp. pp. 456-463). AAAI Press

Lever, G; Laviolette, F; Shawe-Taylor, J; (2010) Distribution-Dependent PAC-Bayes Priors. In: Hutter, M and Stephan, F and Vovk, V and Zeugmann, T, (eds.) (Proceedings) 21st International Conference on Algorithmic Learning Theory (ALT) / 13th International Conference on Discovery Science (DS). (pp. pp. 119-133). SPRINGER-VERLAG BERLIN

Li, S; Shawe-Taylor, J; (2004) Texture Classification by Combining Wavelet and Contourlet Features. In: Fred, ALN and Caelli, T and Duin, RPW and Campilho, AC and Ridder, DD, (eds.) (pp. pp. 1126-1134). Springer

Li, Y; Shawe-Taylor, J; (2004) UNSPECIFIED In: (Proceedings) Using KCCA for Japanese-English corss-language information retrieval and classification.

Li, Y; Shawe-Taylor, J; (2004) Combining Clustering with Canonical Correlation Analysis for Cross-Language Patent Retrieval. In: (Proceedings) Learning Methods for Text Understanding and Mining.

Marchand, M; Su, H; Morvant, E; Rousu, J; Shawe-Taylor, J; (2014) Multilabel structured output learning with random spanning trees of max-margin Markov networks. In: Ghahramani, Z and Welling, M and Cortes, C and Lawrence, ND and Weinberger, KQ, (eds.) [NIPS 2014: Electronic Proceedings of the 25th Neural Information Processing Systems Conference]. Green open access
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Meng, A; Shawe-Taylor, J; (2005) An Investigation of Feature Models for Music Genre Classification Using the Support Vector Classifier. In: (pp. pp. 604-609).

Meng, H; Hardoon, DR; Shawe-Taylor, J; Szedmak, S; (2005) Generic object recognition by combining distinct features in machine learning. In: Nasrabadi, NM and Rizvi, SA, (eds.) (Proceedings) Applications of Neural Networks and Machine Learning in Image Processing IX. (pp. pp. 90-98).

Meng, H; Hardoon, DR; Shawe-Taylor, J; Szedmak, S; (2005) Generic object recognition by combining distinct features in machine learning. In: Nasrabadi, NM and Rizvi, SA, (eds.) (pp. pp. 90-98). SPIE: The International Society for Optical Engineering: Bellingham, US.

Moreau, Y; Preneel, B; Burge, P; Shawe-Taylor, J; Stoermann, C; Cooke, C; (1996) Novel techniques for fraud detection in mobile communications. In: (Proceedings) ACTS Mobile Telecommunications Summit, Granada, Spain.

Pelckmans, K; Shawe-Taylor, J; Suykens, JAK; De Moor, B; (2007) Margin based transductive graph cuts using linear programming. In: (pp. pp. 363-370). Gold open access

Rivasplata, O; Szepesvari, C; Shawe-Taylor, J; Parrado-Hernandez, E; Shiliang, S; (2019) PAC-Bayes bounds for stable algorithms with instance-dependent priors. In: (Proceedings) 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), 2 - 8 December 2018, Montreal, Canada.. (In press).

Rondina, JM; Shawe-Taylor, J; Mourao-Miranda, J; (2013) Stability-based multivariate mapping using SCoRS. In: Davatzikos, C, (ed.) 3rd International Workshop on Pattern Recognition in Neuroimaging (PRNI 2013): Proceedings. (pp. pp. 198-202). IEEE Green open access
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Rosa, MJ; Portugal, L; Shawe-Taylor, J; Mourao-Miranda, J; (2013) Sparse network-based models for patient classification using fMRI. In: (Proceedings) 3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI). (pp. pp. 66-69). IEEE

Rousu, J; Saunders, C; Szedmak, S; Shawe-Taylor, J; (2005) UNSPECIFIED In: (Proceedings) Learning Hierarchical Multi-Category Text Classification Models.

Rousu, J; Saunders, C; Szedmak, S; Shawe-Taylor, J; (2004) UNSPECIFIED In: (Proceedings) On Maximum Margin Hierarchical Classification.

Rousu, J; Saunders, C; Szedmák, S; Shawe-Taylor, J; (2005) Learning hierarchical multi-category text classification models. In: Raedt, LD and Wrobel, S, (eds.) (pp. pp. 744-751). ACM

Saunders, C; Hardoon, DR; Shawe-Taylor, J; Widmer, G; (2008) Using string kernels to identify famous performers from their playing style. In: (pp. pp. 425-440). IOS PRESS

Saunders, C; Hardoon, DR; Shawe-Taylor, J; Widmer, G; (2004) Using String Kernels to Identify Famous Performers from Their Playing Style. In: Boulicaut, J-F and Esposito, F and Giannotti, F and Pedreschi, D, (eds.) (pp. pp. 384-395). Springer

Saunders, C; Shawe-Taylor, J; Vinokourov, A; (2003) UNSPECIFIED In: (Proceedings) String Kernels, Fisher Kernels and Finite State Automata.

Saunders, C; Tschach, H; Shawe-Taylor, J; (2002) Syllables and other string kernel extensions. In: (Proceedings) Nineteenth International Conference on Machine Learning (ICML 2002). (pp. pp. 530-537). Morgan Kaufmann

Schölkopf, B; Williamson, RC; Smola, AJ; Shawe-Taylor, J; Platt, JC; (1999) Support Vector Method for Novelty Detection. In: Solla, SA and Leen, TK and Müller, K-R, (eds.) (pp. pp. 582-588). The MIT Press

Seldin, Y; Laviolette, F; Cesa-Bianchi, N; Shawe-Taylor, J; Auer, P; (2012) PAC-Bayesian Inequalities for Martingales. In: Freitas, ND and Murphy, KP, (eds.) (pp. p. 12). AUAI Press

Shawe-Taylor, J; (2010) Multivariate Bandits and Their Applications. In: Shi, ZZ and Vadera, S and Aamodt, A and Leake, D, (eds.) (Proceedings) 6th IFIP TC12 International Conference on Intelligent Information Processing. (pp. p. 3). SPRINGER-VERLAG BERLIN

Shawe-Taylor, J; Cancedda, N; Cesa-Bianchi, N; Conconi, A; Gentile, C; Goutte, C; Graepel, T; ... Renders, J; + view all (2002) UNSPECIFIED In: (Proceedings) Kernel Methods for Document Filtering. Department of Commerce, National Institute of Standards and Technology

Shawe-Taylor, J; Dolia, A; (2007) A framework for probability density estimation. In: (pp. pp. 468-475). Gold open access

Shawe-Taylor, J; Hardoon, DR; (2009) PAC-Bayes analysis of maximum entropy learning. In: (pp. pp. 480-487). Gold open access

Shawe-Taylor, J; Meng, A; (2005) UNSPECIFIED In: (Proceedings) AN INVESTIGATION OF FEATURE MODELS FOR MUSIC GENRE CLASSIFICATION USING THE SUPPORT VECTOR CLASSIFIER. (pp. pp. 604-609). Queen Mary University of London

Shawe-Taylor, J; Williams, CKI; Cristianini, N; Kandola, JS; (2002) On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum. In: Lange, S and Satoh, K and Smith, CH, (eds.) (pp. p. 12). Springer

Shen, Y; Archambeau, C; Cornford, D; Opper, M; Shawe-Taylor, J; Barillec, R; (2007) Evaluation of variational and Markov Chain Monte Carlo methods for inference in partially observed stochastic dynamic systems. In: (pp. pp. 306-311).

Singh, G; Marshall, IJ; Thomas, J; Shawe-Taylor, J; Wallace, BC; (2017) A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation. In: (Proceedings) ACM Conference on Information and Knowledge Management (CIKM). (pp. pp. 1519-1528). ACM Green open access
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Smith, GE; Diethe, T; Hussain, Z; Shawe-Taylor, J; Hardoon, DR; (2010) Compressed Sampling For Pulse Doppler Radar. In: (Proceedings) 2010 IEEE Radar Conference. (pp. pp. 887-892). IEEE

Specia, L; Turchi, M; Wang, Z; Shawe-Taylor, J; Saunders, C; (2009) Improving the Confidence of Machine Translation Quality Estimates. In: (Proceedings) Machine Translation Summit XII. : Ottawa, Canada.

Szedmák, S; Shawe-Taylor, J; (2006) Synthesis of maximum margin and multiview learning using unlabeled data. In: (pp. pp. 479-484).

Tsampouka, P; Shawe-Taylor, J; (2005) Analysis of Generic Perceptron-Like Large Margin Classifiers. In: Gama, J and Camacho, R and Brazdil, P and Jorge, A and Torgo, L, (eds.) (pp. pp. 750-758). Springer

Vinokourov, A; Hardoon, D; Shawe-Taylor, J; (2003) Learning the semantics of multimedia content with application to web image retrieval and classification. In: (Proceedings) Fourth International Symposium on Independent Component Analysis and Blind Source Separation, 2003.

Wang, Z; Shawe-Taylor, J; (2009) Large-margin structured prediction via linear programming. In: (pp. pp. 599-606). Gold open access

Wang, Z; Shawe-Taylor, J; (2008) Kernel Regression Framework for Machine Translation: UCL System Description for WMT 2008 Shared Translation Task. In: (Proceedings) The Third ACL Workshop on Statistical Machine Translation. (pp. pp. 155-158). Association for Computational Linguistics: Columbus, Ohio, USA.

Wang, Z; Shawe-Taylor, J; Szedmák, S; (2007) Kernel Regression Based Machine Translation. In: Sidner, CL and Schultz, T and Stone, M and Zhai, C, (eds.) (pp. pp. 185-188). The Association for Computational Linguistics Green open access
file

Wood, J; Shawe-Taylor, J; (1995) UNSPECIFIED In: (Proceedings) Neural Networks for Invariant Pattern Recognition. (pp. pp. 253-258).

Wood, J; Shawe-Taylor, J; (1995) Neural networks for invariant pattern recognition. In:

Report

Ambroladze, A; Shawe-Taylor, J; (2005) Core Skills curriculum for Information Technology. (Report for the Curriculum Development Programme of the PASCAL Network of Excellence ).

Anthony, M; Shawe-Taylor, J; (1993) Generalising from Approximate Interpolation.

Cesa-Bianchi, N; Grunwald, P; Gunn, S; Sebag, M; Shawe-Taylor, J; Triggs, B; (2007) Managing a Large network of excellence: Case Study of the PASCAL Network. (Report of the PASCAL Network of Excellence for the European Commission ).

Dolia, AN; Harris, CJ; Shawe-Taylor, JS; Titterington, DM; (2007) Kernel ellipsoidal trimming. ELSEVIER SCIENCE BV

Domingo, C; Shawe-Taylor, J; Bodlaender, H; Abello, J; (1994) Learning Minor Closed Graph Classes with Membership and Equivalence Queries.

Hardoon, D; Hussain, Z; Shawe-Taylor, J; (2009) A Nonconformity Approach to Model Selection for SVMs.

Kandola, J; Shawe-Taylor, J; Cristianini, N; (2002) On the Extensions of Kernel Alignment.

Kandola, J; Shawe-Taylor, J; Cristianini, N; (2002) Optimizing Kernel Alignment over Combinations of Kernel.

Riess, P; Shawe-Taylor, J; (1989) The RSA Public Key Cryptosystem.

Shawe-Taylor, J; (1992) Mean Field Annealing as a Barrier Function Optimisation and Alternative Solution Strategies.

Shawe-Taylor, J; (1991) The Asymptotic Equipartition Property for Two dimensional Ergodic Arrays.

Shawe-Taylor, J; (1988) Consultancy Report on Feasibility of Applying Neural Network Techniques to Unmanned Vehicle Control.

Shawe-Taylor, J; Cristianini, N; (1998) Robust Bounds on Generalization from the Margin Distribution.

Shawe-Taylor, J; De Bil, T; Cristianini, N; (2006) Data mining, data fusion and information management. (Foresight Project on Intelligent Infrastructure Systems ).

Shawe-Taylor, J; Pisanski, T; (1993) Characterising Graph Drawing with Eigenvectors.

Shawe-Taylor, J; Zerovnik, J; (1993) Analysis of the Mean Field Annealing Algorithm for Graph Colouring.

Tsampouka, P; Shawe-Taylor, J; (2007) Approximate maximum margin algorithms with rules controlled by the number of mistakes. (Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007 , pp. pp. 903-910 ). ACM

Tsampouka, P; Shawe-Taylor, J; (2006) Constant Rate Approximate Maximum Margin Algorithms. (Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings , pp. pp. 437-448 ). Springer

Wood, J; Shawe-Taylor, J; (1993) Theory of symmetry network structure.

Conference item

Chain, B; Best, K; Cinelli, M; Friedman, N; Mark, M; Reich-Zeliger, S; Sun, Y; ... Shifrut, E; + view all (2016) Characterisation of the T cell receptor repertoire following immunisation. Presented at: International Congress of Immunology (ICI), Melbourne, AUSTRALIA.

Johnston, M; Michie, S; West, R; Thomas, J; Mac Aonghusa, P; Shawe-Taylor, J; Kelly, M; (2017) THE HUMAN BEHAVIOUR CHANGE PROJECT: DEVELOPMENT OF AN AUTOMATED SYSTEM TO SYNTHESISE EVALUATIONS OF BEHAVIOUR CHANGE INTERVENTIONS TO FURTHER THE SCIENCE AND APPLICATION OF BEHAVIOUR CHANGE. Presented at: 75th Annual Scientific Meeting on Mobilizing Technology to Advance Biobehavioral Science and Health, Sevilla, Spain.

Other

Hardoon, D; Shawe-Taylor, J; Friman, O; (2004) KCCA Feature Selection for fMRI Analysis. UNSPECIFIED

Saunders, C; Gunn, S; Grobelnik, M; Shawe-Taylor, J; Subspace, Latent Structure and Feature Selection techniques. UNSPECIFIED

Shawe-Taylor, J; (1987) The Semantics and Open Set Analysis of a First Order Programming Language. UNSPECIFIED

Shawe-Taylor, J; (1985) Regularity and Transitivity in Graphs. UNSPECIFIED

Shawe-Taylor, J; (1982) Linearen Algoritem za Testiranje Planarnosti Grafov, (Linear Time Algorithm for Testing Graph Planarity). UNSPECIFIED

Shawe-Taylor, J; Archambeau, C; Opper, M; PAC-Bayes Analysis of Stochastic Differntial Equation Modelling. UNSPECIFIED

Szedmak, S; Shawe-Taylor, J; (2005) Multiclass Learning at One-class Complexity. UNSPECIFIED

Tsampouka, P; Shawe-Taylor, J; (2005) Perceptron-like Large Margin Classifiers. UNSPECIFIED

Wang, Z; Shawe-Taylor, J; Szedmak, S; (2007) Kernel regression based machine translation. Association for Computational Linguistics, Rochester, NY, USA East Stroudsburg, PA, USA.

This list was generated on Sun Apr 21 16:48:17 2019 BST.