John Shawe-Taylor
John Shawe-Taylor
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Cited by
Support Vector Machines
N Cristianini, J Shawe-Taylor
Cambridge: Cambridge University Press, 2000
The pascal visual object classes (voc) challenge
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
International journal of computer vision 88 (2), 303-338, 2010
Kernel methods for pattern analysis
J Shawe-Taylor, N Cristianini
Cambridge university press, 2004
Estimating the support of a high-dimensional distribution
B Schölkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson
Neural computation 13 (7), 1443-1471, 2001
Canonical correlation analysis: An overview with application to learning methods
DR Hardoon, S Szedmak, J Shawe-Taylor
Neural computation 16 (12), 2639-2664, 2004
Large margin dags for multiclass classification.
JC Platt, N Cristianini, J Shawe-Taylor
nips 12, 547-553, 1999
Support vector method for novelty detection.
B Schölkopf, RC Williamson, AJ Smola, J Shawe-Taylor, JC Platt
NIPS 12, 582-588, 1999
Text classification using string kernels
H Lodhi, C Saunders, J Shawe-Taylor, N Cristianini, C Watkins
Journal of Machine Learning Research 2 (Feb), 419-444, 2002
On kernel target alignment
N Cristianini, J Kandola, A Elisseeff, J Shawe-Taylor
Innovations in machine learning, 205-256, 2006
Challenges in representation learning: A report on three machine learning contests
IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ...
International conference on neural information processing, 117-124, 2013
Structural risk minimization over data-dependent hierarchies
J Shawe-Taylor, PL Bartlett, RC Williamson, M Anthony
IEEE transactions on Information Theory 44 (5), 1926-1940, 1998
An introduction to support vector machines and other kernel-based learning methods
J Shawe-Taylor, N Cristianini
Volume, 2000
Linear programming boosting via column generation
A Demiriz, KP Bennett, J Shawe-Taylor
Machine Learning 46 (1), 225-254, 2002
Generalization performance of support vector machines and other pattern classifiers
P Bartlett, J Shawe-Taylor
Advances in kernel methods: support vector learning, 43-54, 1999
Latent semantic kernels
N Cristianini, J Shawe-Taylor, H Lodhi
Journal of Intelligent Information Systems 18 (2), 127-152, 2002
Two view learning: SVM-2K, theory and practice
J Farquhar, D Hardoon, H Meng, JS Shawe-Taylor, S Szedmak
Advances in neural information processing systems, 355-362, 2006
Kernel-based learning of hierarchical multilabel classification models.
J Rousu, C Saunders, S Szedmak, J Shawe-Taylor, KP Bennett, ...
Journal of Machine Learning Research 7 (7), 2006
An introduction to support vector machine
N Cristianini, J Shawe-Taylor
Cambridge university press, 2000
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges Workshop, 117-176, 2005
Inferring a semantic representation of text via cross-language correlation analysis
A Vinokourov, N Cristianini, J Shawe-Taylor
Advances in neural information processing systems 15, 1497-1504, 2002
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