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2010 – 2019
- 2011
[j12]Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien:
lp-Norm Multiple Kernel Learning. J. Mach. Learn. Res. 12: 953-997 (2011)- [c16]Robert Jenssen, Marius Kloft, Sören Sonnenburg, Alexander Zien, Klaus-Robert Müller
:
A new scatter-based multi-class support vector machine. MLSP 2011: 1-6 - [c15]Nico Görnitz, Christian Widmer, Georg Zeller, André Kahles, Sören Sonnenburg, Gunnar Rätsch:
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation. NIPS 2011: 2690-2698 - 2010
- [j11]Sören Sonnenburg, Gunnar Rätsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio De Bona, Alexander Binder, Christian Gehl, Vojtech Franc:
The SHOGUN Machine Learning Toolbox. J. Mach. Learn. Res. 11: 1799-1802 (2010) - [c14]Sören Sonnenburg, Vojtech Franc:
COFFIN: A Computational Framework for Linear SVMs. ICML 2010: 999-1006 - [i1]Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien:
Non-Sparse Regularization and Efficient Training with Multiple Kernels. CoRR abs/1003.0079 (2010)
2000 – 2009
- 2009
- [j10]Vojtech Franc, Sören Sonnenburg:
Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization. J. Mach. Learn. Res. 10: 2157-2192 (2009) - [j9]Gabriele Beate Schweikert, Jonas Behr, Alexander Zien, Georg Zeller, Cheng Soon Ong, Sören Sonnenburg, Gunnar Rätsch:
mGene.web: a web service for accurate computational gene finding. Nucleic Acids Res. 37(Web-Server-Issue): 312-316 (2009) - [c13]Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien:
Efficient and Accurate Lp-Norm Multiple Kernel Learning. NIPS 2009: 997-1005 - [c12]Alexander Zien, Nicole Krämer, Sören Sonnenburg, Gunnar Rätsch:
The Feature Importance Ranking Measure. ECML/PKDD (2) 2009: 694-709 - 2008
- [b1]Sören Sonnenburg:
Machine learning for genomic sequence analysis. Berlin Institute of Technology, 2008 - [j8]Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch:
Support Vector Machines and Kernels for Computational Biology. PLoS Comput. Biol. 4(10) (2008) - [c11]Vojtech Franc, Sören Sonnenburg:
Optimized cutting plane algorithm for support vector machines. ICML 2008: 320-327 - [c10]Sören Sonnenburg, Alexander Zien, Petra Philips, Gunnar Rätsch:
POIMs: positional oligomer importance matrices - understanding support vector machine-based signal detectors. ISMB 2008: 6-14 - [p1]Sören Sonnenburg:
Maschinelles Lernen zur Genom-Sequenzanalyse [Machine Learning for Genomic Sequence Analysis]. Ausgezeichnete Informatikdissertationen 2008: 281-290 - 2007
- [j7]Sören Sonnenburg, Gabriele Beate Schweikert, Petra Philips, Jonas Behr, Gunnar Rätsch:
Accurate splice site prediction using support vector machines. BMC Bioinform. 8(S-10) (2007) - [j6]Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - [j5]Gunnar Rätsch, Sören Sonnenburg, Jagan Srinivasan, Hanh Witte, Klaus-Robert Müller, Ralf J. Sommer, Bernhard Schölkopf:
Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning. PLoS Comput. Biol. 3(2) (2007) - 2006
- [j4]Gunnar Rätsch, Sören Sonnenburg, Christin Schäfer:
Learning Interpretable SVMs for Biological Sequence Classification. BMC Bioinform. 7(S-1) (2006) - [j3]Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf:
Large Scale Multiple Kernel Learning. J. Mach. Learn. Res. 7: 1531-1565 (2006) - [c9]Sören Sonnenburg, Alexander Zien, Gunnar Rätsch:
ARTS: accurate recognition of transcription starts in human. ISMB (Supplement of Bioinformatics) 2006: 472-480 - [c8]Gunnar Rätsch, Sören Sonnenburg:
Large Scale Hidden Semi-Markov SVMs. NIPS 2006: 1161-1168 - [c7]Konrad Rieck, Pavel Laskov, Sören Sonnenburg:
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees. NIPS 2006: 1177-1184 - 2005
- [j2]Klaus-Robert Müller, Gunnar Rätsch, Sören Sonnenburg, Sebastian Mika, Michael Grimm, Nikolaus Heinrich:
Classifying 'Drug-likeness' with Kernel-Based Learning Methods. J. Chem. Inf. Model. 45(2): 249-253 (2005) - [c6]Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf:
Large scale genomic sequence SVM classifiers. ICML 2005: 848-855 - [c5]Gunnar Rätsch, Sören Sonnenburg, Bernhard Schölkopf:
RASE: recognition of alternatively spliced exons in C.elegans. ISMB (Supplement of Bioinformatics) 2005: 369-377 - [c4]Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer:
A General and Efficient Multiple Kernel Learning Algorithm. NIPS 2005: 1273-1280 - [c3]Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer:
Learning Interpretable SVMs for Biological Sequence Classification. RECOMB 2005: 389-407 - 2002
- [j1]Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller:
A New Discriminative Kernel from Probabilistic Models. Neural Comput. 14(10): 2397-2414 (2002) - [c2]Sören Sonnenburg, Gunnar Rätsch, Arun K. Jagota, Klaus-Robert Müller:
New Methods for Splice Site Recognition. ICANN 2002: 329-336 - 2001
- [c1]Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller:
A New Discriminative Kernel From Probabilistic Models. NIPS 2001: 977-984
Coauthor Index
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