| Support Vector Machines N Cristianini, J Shawe-Taylor Cambridge: Cambridge University Press, 2000 | 21744 | 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, 303-338, 2010 | 21420 | 2010 |
| Kernel methods for pattern analysis J Shawe-Taylor, N Cristianini Cambridge university press, 2004 | 8929 | 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 | 4971 | 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 | 3497 | 2004 |
| Large margin DAGs for multiclass classification J Platt, N Cristianini, J Shawe-Taylor Advances in neural information processing systems 12, 1999 | 2894 | 1999 |
| Estimating the support of a high-dimensional distribution JC Platt, JS Shawe-Taylor, AJ Smola, RC Williamson Neural computation 13 (7), 1443-1471, 2001 | 2274 | 2001 |
| Support vector method for novelty detection B Schölkopf, RC Williamson, A Smola, J Shawe-Taylor, J Platt Advances in neural information processing systems 12, 1999 | 2059 | 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 | 2000 | 2002 |
| Challenges in representation learning: A report on three machine learning contests IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ... Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 1483 | 2013 |
| On kernel-target alignment N Cristianini, J Shawe-Taylor, A Elisseeff, J Kandola Advances in neural information processing systems 14, 2001 | 1341 | 2001 |
| An introduction to support vector machines and other kernel-based learning methods J Shawe-Taylor, N Cristianini Volume, 2000 | 793* | 2000 |
| 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 | 714 | 1998 |
| Linear programming boosting via column generation A Demiriz, KP Bennett, J Shawe-Taylor Machine Learning 46, 225-254, 2002 | 563 | 2002 |
| Support vector method for novelty detection B Scholkopf, R Williamson, A Smola, J Shawe-Taylor, J Platt Advances in neural information processing systems 12 (3), 582-588, 2000 | 555 | 2000 |
| 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 | 459 | 1999 |
| Latent semantic kernels N Cristianini, J Shawe-Taylor, H Lodhi Journal of Intelligent Information Systems 18, 127-152, 2002 | 412 | 2002 |
| Two view learning: SVM-2K, theory and practice J Farquhar, D Hardoon, H Meng, J Shawe-Taylor, S Szedmak Advances in neural information processing systems 18, 2005 | 406 | 2005 |
| Empirical risk minimization under fairness constraints M Donini, L Oneto, S Ben-David, JS Shawe-Taylor, M Pontil Advances in neural information processing systems 31, 2018 | 377 | 2018 |
| Kernel-based learning of hierarchical multilabel classification models J Rousu, C Saunders, S Szedmak, J Shawe-Taylor Journal of Machine Learning Research 7, 1601-1626, 2006 | 351 | 2006 |
Nello CristianiniUniversity of BathVerified email at bath.ac.uk
