| Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf The Journal of Machine Learning Research 7, 1531-1565, 2006 | 1739 | 2006 |
| Support vector machines and kernels for computational biology A Ben-Hur, CS Ong, S Sonnenburg, B Schölkopf, G Rätsch PLoS computational biology 4 (10), e1000173, 2008 | 816 | 2008 |
| lp-Norm Multiple Kernel Learning M Kloft, U Brefeld, S Sonnenburg, A Zien The Journal of Machine Learning Research 12, 953-997, 2011 | 466 | 2011 |
| The SHOGUN machine learning toolbox S Sonnenburg, G Rätsch, S Henschel, C Widmer, J Behr, A Zien, F Bona, ... The Journal of Machine Learning Research 11, 1799-1802, 2010 | 408 | 2010 |
| Efficient and accurate lp-norm multiple kernel learning M Kloft, U Brefeld, P Laskov, KR Müller, A Zien, S Sonnenburg Advances in neural information processing systems 22, 2009 | 357 | 2009 |
| The need for open source software in machine learning S Sonnenburg, ML Braun, CS Ong, S Bengio, L Bottou, G Holmes, ... | 273 | 2007 |
| Accurate splice site prediction using support vector machines S Sonnenburg, G Schweikert, P Philips, J Behr, G Rätsch BMC bioinformatics 8, 1-16, 2007 | 248 | 2007 |
| A general and efficient multiple kernel learning algorithm S Sonnenburg, G Rätsch, C Schäfer Advances in neural information processing systems 18, 2005 | 234 | 2005 |
| A new discriminative kernel from probabilistic models K Tsuda, M Kawanabe, G Rätsch, S Sonnenburg, KR Müller Advances in Neural Information Processing Systems 14, 2001 | 213 | 2001 |
| Optimized cutting plane algorithm for support vector machines V Franc, S Sonnenburg Proceedings of the 25th international conference on Machine learning, 320-327, 2008 | 184 | 2008 |
| RASE: recognition of alternatively spliced exons in C.elegans G Rätsch, S Sonnenburg, B Schölkopf Bioinformatics 21 (suppl_1), i369-i377, 2005 | 182 | 2005 |
| ARTS: accurate recognition of transcription starts in human S Sonnenburg, A Zien, G Rätsch Bioinformatics 22 (14), e472-e480, 2006 | 173 | 2006 |
| The feature importance ranking measure A Zien, N Krämer, S Sonnenburg, G Rätsch Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009 | 169 | 2009 |
| Non-sparse multiple kernel learning M Kloft, U Brefeld, P Laskov, S Sonnenburg NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels 4, 5, 2008 | 134 | 2008 |
| 13 Accurate Splice Site Detection for Caenorhabditis elegans G Rätsch, S Sonnenburg Kernel methods in computational biology 277, 2004 | 125 | 2004 |
| Classifying ‘drug-likeness' with kernel-based learning methods KR Müller, G Rätsch, S Sonnenburg, S Mika, M Grimm, N Heinrich Journal of chemical information and modeling 45 (2), 249-253, 2005 | 122 | 2005 |
| mGene: accurate SVM-based gene finding with an application to nematode genomes G Schweikert, A Zien, G Zeller, J Behr, C Dieterich, CS Ong, P Philips, ... Genome research 19 (11), 2133-2143, 2009 | 119 | 2009 |
| Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning G Rätsch, S Sonnenburg, J Srinivasan, H Witte, KR Müller, RJ Sommer, ... PLoS Computational Biology 3 (2), e20, 2007 | 119 | 2007 |
| Learning interpretable SVMs for biological sequence classification G Rätsch, S Sonnenburg, C Schäfer BMC bioinformatics 7, 1-14, 2006 | 102 | 2006 |
| New methods for splice site recognition S Sonnenburg, G Rätsch, A Jagota, KR Müller Artificial Neural Networks—ICANN 2002: International Conference Madrid …, 2002 | 100 | 2002 |
Gunnar RätschProfessor, ETH Zürich在 inf.ethz.ch 的电子邮件经过验证
