Soeren Sonnenburg

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Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Cheng Soon OngData61, CSIRO, CanberraVerified email at anu.edu.au
Marius KloftProfessor, RPTU Kaiserslautern-LandauVerified email at cs.uni-kl.de
Christin Schäferacs plus GmbHVerified email at acs-plus.de
Vojtech FrancCzech Technical UniversityVerified email at cmp.felk.cvut.cz
Jonas BehrSOPHiA GENETICS, St.-Sulpice, SwitzerlandVerified email at sophiagenetics.com
Ulf BrefeldLeuphana Universität LüneburgVerified email at leuphana.de
Gabriele SchweikertPI, University of Dundee, UK and Universität Tübingen, GermanyVerified email at dundee.ac.uk
Pavel LaskovUniversity of LiechtensteinVerified email at uni.li
Asa Ben-HurComputer Science, Colorado State UniversityVerified email at cs.colostate.edu
Georg ZellerEMBL, HeidelbergVerified email at embl.de
Mikio L. BraunTU Berlin (allumni)Verified email at zalando.de
Christian WidmerGoogleVerified email at google.com
Jagan SrinivasanDept. of Biology and Biotechnology, Worcester Polytechnic InstituteVerified email at wpi.edu
Ralf SommerDirector, Max-Planck Institute for Developmental BiologyVerified email at tuebingen.mpg.de
Konrad RieckTechnische Universität BerlinVerified email at tu-berlin.de
Alexander BinderChair Computer Vision, OvGU, Magdeburg, GermanyVerified email at ovgu.de
Sebastian MikaVerified email at sebastianmika.info

Soeren Sonnenburg

Machine Learning Researcher

Verified email at tomtom.com - Homepage

Machine Learning Computational Biology Traffic


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf The Journal of Machine Learning Research 7, 1531-1565, 2006	1748	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	838	2008
l_p-Norm Multiple Kernel Learning M Kloft, U Brefeld, S Sonnenburg, A Zien The Journal of Machine Learning Research 12, 953-997, 2011	473	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	413	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	359	2009
The need for open source software in machine learning S Sonnenburg, ML Braun, CS Ong, S Bengio, L Bottou, G Holmes, ...	281	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	251	2007
A general and efficient multiple kernel learning algorithm S Sonnenburg, G Rätsch, C Schäfer Advances in neural information processing systems 18, 2005	235	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	214	2001
The feature importance ranking measure A Zien, N Krämer, S Sonnenburg, G Rätsch Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009	188	2009
Optimized cutting plane algorithm for support vector machines V Franc, S Sonnenburg Proceedings of the 25th international conference on Machine learning, 320-327, 2008	185	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	174	2006
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	120	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	103	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

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