| An introduction to support vector machines and other kernel-based learning methods N Cristianini, J Shawe-Taylor Cambridge university press, 2000 | 23258 | 2000 |
| Kernel methods for pattern analysis J Shawe-Taylor, N Cristianini Cambridge university press, 2004 | 8584 | 2004 |
| Support vector machine classification and validation of cancer tissue samples using microarray expression data TS Furey, N Cristianini, N Duffy, DW Bednarski, M Schummer, D Haussler Bioinformatics 16 (10), 906-914, 2000 | 3134 | 2000 |
| Knowledge-based analysis of microarray gene expression data by using support vector machines MPS Brown, WN Grundy, D Lin, N Cristianini, CW Sugnet, TS Furey, ... Proceedings of the National Academy of Sciences 97 (1), 262-267, 2000 | 3110 | 2000 |
| Learning the kernel matrix with semidefinite programming GRG Lanckriet, N Cristianini, P Bartlett, LE Ghaoui, MI Jordan Journal of Machine learning research 5 (Jan), 27-72, 2004 | 2974 | 2004 |
| Large margin DAGs for multiclass classification J Platt, N Cristianini, J Shawe-Taylor Advances in neural information processing systems 12, 1999 | 2854 | 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 | 1933 | 2002 |
| On kernel-target alignment N Cristianini, J Shawe-Taylor, A Elisseeff, J Kandola Advances in neural information processing systems 14, 2001 | 1272 | 2001 |
| Core vector machines: Fast SVM training on very large data sets. IW Tsang, JT Kwok, PM Cheung, N Cristianini Journal of Machine Learning Research 6 (4), 2005 | 1269 | 2005 |
| Controlling the sensitivity of support vector machines K Veropoulos, C Campbell, N Cristianini Proceedings of the international joint conference on AI 55, 60, 1999 | 1007 | 1999 |
| On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning. P Drineas, MW Mahoney, N Cristianini journal of machine learning research 6 (12), 2005 | 1001 | 2005 |
| CAFE: a computational tool for the study of gene family evolution T De Bie, N Cristianini, JP Demuth, MW Hahn Bioinformatics 22 (10), 1269-1271, 2006 | 950 | 2006 |
| A statistical framework for genomic data fusion GRG Lanckriet, T De Bie, N Cristianini, MI Jordan, WS Noble Bioinformatics 20 (16), 2626-2635, 2004 | 849 | 2004 |
| Fast kernel classifiers with online and active learning. A Bordes, S Ertekin, J Weston, L Botton, N Cristianini Journal of Machine Learning Research 6 (9), 2005 | 814 | 2005 |
| Query learning with large margin classifiers C Campbell, N Cristianini, A Smola ICML 20 (0), 0, 2000 | 505 | 2000 |
| Tracking the flu pandemic by monitoring the social web V Lampos, N Cristianini 2010 2nd international workshop on cognitive information processing, 411-416, 2010 | 462 | 2010 |
| The kernel-adatron algorithm: a fast and simple learning procedure for support vector machines TT Frie, N Cristianini, C Campbell Machine learning: proceedings of the fifteenth international conference …, 1998 | 453 | 1998 |
| Kernel-based data fusion and its application to protein function prediction in yeast GRG Lanckriet, M Deng, N Cristianini, MI Jordan, WS Noble Biocomputing 2004, 300-311, 2003 | 410 | 2003 |
| Latent semantic kernels N Cristianini, J Shawe-Taylor, H Lodhi Journal of Intelligent Information Systems 18 (2), 127-152, 2002 | 405 | 2002 |
| Dimension reduction in text classification with support vector machines. H Kim, P Howland, H Park, N Christianini Journal of machine learning research 6 (1), 2005 | 357 | 2005 |
John Shawe-TaylorUCLE-mail confirmado em cs.ucl.ac.uk
