Proceedings (1): |
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Bousquet O  , von Luxburg U and Rätsch G : Advanced Lectures on Machine Learning, ML Summer Schools 2003, 240, Springer, Berlin, Germany, (2004).
978-3-540-23122-6
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Articles (30): |
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Widmer C and Rätsch G (2012) Multitask Learning in Computational Biology
JMLR W&CP. ICML 2011 Unsupervised and Transfer Learning Workshop 27 207--216.
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Gan XC , Stegle O , Behr J , Steffen JG , Drewe P , Hildebrand KL , Lyngsoe R , Schultheiss SJ , Osborne EJ , Sreedharan VT , Kahles A , Bohnert R , Jean G , Derwent P , Kersey P , Belfield EJ , Harberd NP , Kemen E , Toomajian C , Kover PX , Clark RM , Rätsch G and Mott R (2011) Multiple reference genomes and transcriptomes for Arabidopsis thaliana
Nature 477(7365) 419–423.
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Stegle O , Drewe P , Bohnert R , Borgwardt K and Rätsch G (2010) Statistical Tests for Detecting Differential RNA-Transcript Expression from Read Counts
Nature Precedings 2010 1-11.
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Widmer C , Toussaint NC , Altun Y and Rätsch G (2010) Inferring latent task structure for Multitask Learning by Multiple Kernel Learning
BMC Bioinformatics 11 Suppl 8 S5.
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Graf ABA , Bousquet O , Rätsch G and Schölkopf B (2009) Prototype Classification: Insights from Machine Learning
Neural Computation 21(1) 272-300.
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Schweikert G , Zien A , Zeller G , Behr J , Dieterich C , Ong CS , Philips P , De Bona F , Hartmann L , Bohlen A , Krüger N , Sonnenburg S and Rätsch G (2009) mGene: accurate SVM-based gene finding with an application to nematode genomes
Genome Research 19(11) 2133-43.
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Schweikert G , Behr J , Zien A , Zeller G , Ong CS , Sonnenburg S and Rätsch G (2009) mGene.web: a web service for accurate computational gene finding
Nucleic Acids Research 37 W312-6.
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Ben-Hur A , Ong CS , Sonnenburg S , Schölkopf B and Rätsch G (2008) Support Vector Machines and Kernels for Computational Biology
PLoS Computational Biology 4(10: e1000173) 1-10.
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Laubinger S , Zeller G , Henz SR , Sachsenberg T , Widmer CK , Naouar N , Vuylsteke M , Schölkopf B , Rätsch G and Weigel D (2008) At-TAX: A Whole Genome Tiling Array Resource for Developmental Expression Analysis and Transcript Identification in Arabidopsis thaliana
Genome Biology 9(7: R112) 1-16.
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Sonnenburg S , Schweikert G , Philips P , Behr J and Rätsch G (2007) Accurate Splice site Prediction Using Support Vector Machines
BMC Bioinformatics 8(Supplement 10) 1-16.
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Sonnenburg S , Braun ML , Ong CS , Bengio S , Bottou L , Holmes G , LeCun Y , Müller K-R , Pereira F , Rasmussen CE , Rätsch G , Schölkopf B , Smola A , Vincent P , Weston J and Williamson RC (2007) The Need for Open Source Software in Machine Learning
Journal of Machine Learning Research 8 2443-2466.
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Clark RM , Schweikert G , Toomajian C , Ossowski S , Zeller G , Shinn P , Warthmann N , Hu TT , Fu G , Hinds DA , Chen H , Frazer KA , Huson DH , Schölkopf B , Nordborg M , Rätsch G , Ecker JR and Weigel D (2007) Common Sequence Polymorphisms Shaping Genetic Diversity in Arabidopsis thaliana
Science 317(5836) 338-342.
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Schulze U , Hepp B , Ong CS and Rätsch G (2007) PALMA: mRNA to Genome Alignments using Large Margin Algorithms
Bioinformatics 23(15) 1892-1900.
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Rätsch G , Sonnenburg S , Srinivasan J , Witte H , Müller K-R , Sommer R-J and Schölkopf B (2007) Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning
PLoS Computational Biology 3(2, e20) 0313-0322.
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Sonnenburg S , Zien A and Rätsch G (2006) ARTS: Accurate Recognition of Transcription Starts in Human
Bioinformatics 22(14) e472-e480.
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Sonnenburg S , Rätsch G , Schäfer C and Schölkopf B (2006) Large Scale Multiple Kernel Learning
Journal of Machine Learning Research 7 1531-1565.
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Tsuda K and Rätsch G (2005) Image Reconstruction by Linear Programming
IEEE Transactions on Image Processing 14(6) 737-744.
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Tsuda K , Rätsch G and Warmuth M (2005) Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection
Journal of Machine Learning Research 6 995-1018.
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Rätsch G , Sonnenburg S and Schölkopf B (2005) RASE: recognition of alternatively spliced exons in C.elegans
Bioinformatics 21(Suppl. 1) i369-i377.
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Mika S , Rätsch G , Weston J , Schölkopf B , Smola AJ and Müller K-R (2003) Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence 25(5) 623-628.
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Warmuth MK , Liao J , Rätsch G , Mathieson M , Putta S and Lemmen C (2003) Active Learning with SVMs in the Drug Discovery Process
Chemical Information and Computer Sciences 43(2) 667ß673-667ß673.
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Tsuda K , Kawanabe M , Rätsch G , Sonnenburg S and Müller KR (2002) A New Discriminative Kernel from Probabilistic Models
Neural Computation 14(10) 2397-2414.
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Rätsch G , Mika S , Schölkopf B and Müller K-R (2002) Constructing Boosting algorithms from SVMs: an application to one-class classification.
IEEE Transactions on Pattern Analysis and Machine Intelligence 24(9) 1184-1199.
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Rätsch G , Demiriz A and Bennett K (2002) Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Machine Learning 48 193-221.
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Müller K-R , Mika S , Rätsch G , Tsuda K and Schölkopf B (2001) An Introduction to Kernel-Based Learning Algorithms
IEEE Transactions on Neural Networks 12(2) 181-201.
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Onoda T , Rätsch G and Müller KR (2001) An Arcing algorithm with an intuitive learning control parameter
Journal of the Japanese Society for AI 16(5C) 417-426.
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Rätsch G , Onoda T and Müller KR (2001) Soft margins for AdaBoost
Machine Learning 42 287-320.
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Zien A , Rätsch G , Mika S , Schölkopf B , Lengauer T and Müller K-R (2000) Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites
Bioinformatics 16(9) 799-807.
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Onoda T , Rätsch G and Müller KR (2000) An asymptotical Analysis and Improvement of AdaBoost in the binary classification case
Journal of the Japanese Society for AI 15(2) 287-296.
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Schölkopf B , Mika S , Burges CJC , Knirsch P , Müller K-R , Rätsch G and Smola AJ (1999) Input space versus feature space in kernel-based methods
IEEE Transactions On Neural Networks 10(5) 1000-1017.
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Conference papers (27): |
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Widmer C , Kloft M , Görnitz N and Rätsch G (2012) Efficient Training of Graph-Regularized Multitask SVMs
In: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML/PKDD 2012, LNCS Vol. 7523, (Ed) PA Flach, T De Bie and N Cristianini, ECML 2012, Springer, Berlin, Germany, 633-647.
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Görnitz N , Widmer C , Zeller G , Kahles A , Sonnenburg S and Rätsch G (2011) Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation
In: Advances in Neural Information Processing Systems 24, (Ed) J Shawe-Taylor, RS Zemel, P Bartlett, FCN Pereira and KQ Weinberger, Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Curran Associates, Inc., Red Hook, NY, USA, 2690--2698.
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Widmer C , Leiva J , Altun Y and Rätsch G (2010) Leveraging Sequence Classification by Taxonomy-based Multitask Learning
In: Research in Computational Molecular Biology, LNCS, Vol. 6044, (Ed) B Berger, 14th Annual International Conference, RECOMB 2010, Springer, Berlin, Germany, 522--534.
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Widmer C , Toussaint NC , Altun Y , Kohlbacher O and Rätsch G (2010) Novel machine learning methods for MHC Class I binding prediction
In: Pattern Recognition in Bioinformatics, (Ed) TMH Dijkstra, E Tsivtsivadze, E Marchiori and T Heskes, 5th IAPR International Conference, PRIB 2010, Springer, Berlin, Germany, 98--109.
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Schweikert G , Widmer C , Schölkopf B and Rätsch G (2009) An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis
In: Advances in neural information processing systems 21, (Ed) D Koller, D Schuurmans, Y Bengio and L Bottou, 22nd Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 1433-1440.
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Shin H , Hill NJ and Rätsch G (2006) Graph Based Semi-Supervised Learning with Sharper Edges
In: ECML 2006, (Ed) Fürnkranz, J. , T. Scheffer, M. Spiliopoulou, 17th European Conference on Machine Learning (ECML), Springer, Berlin, Germany, 401-412.
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Rätsch G , Hepp B , Schulze U and Ong CS (2006) PALMA: Perfect Alignments using Large Margin Algorithms
In: GCB 2006, (Ed) Huson, D. , O. Kohlbacher, A. Lupas, K. Nieselt, A. Zell, German Conference on Bioinformatics 2006, Gesellschaft für Informatik, Bonn, Germany, 104-113.
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Tsuda K , Rätsch G and Warmuth MK (2005) Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection
In: Advances in Neural Information Processing Systems 17, (Ed) Saul, L.K. , Y. Weiss, L. Bottou, Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), MIT Press, Cambridge, MA, USA, 1425-1432.
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Sonnenburg S , Rätsch G and Schölkopf B (2005) Large Scale Genomic Sequence SVM Classifiers
In: Proceedings of the 22nd International Conference on Machine Learning, (Ed) L De Raedt and S Wrobel, ICML 2005, ACM, New York, NY, USA, 849-856.
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Tsuda K and Rätsch G (2004) Image Construction by Linear Programming
In: Advances in Neural Information Processing Systems 16, (Ed) Thrun, S., L.K. Saul, B. Schölkopf, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 57-64.
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Rätsch G , Smola A and Mika S (2003) Adapting Codes and Embeddings for Polychotomies
In: Advances in Neural Information Processing Systems 15, (Ed) Becker, S. , S. Thrun, K. Obermayer, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 513-520.
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Tsuda K , Kawanabe M , Rätsch G , Sonnenburg S and Müller K-R (2002) A new discriminative kernel from probabilistic models
In: Advances in Neural Information Processing Systems 14, (Ed) Dietterich, T.G. , S. Becker, Z. Ghahramani, Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), MIT Press, Cambridge, MA, USA, 977-984.
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Warmuth MK , Rätsch G , Mathieson M , Liao J and Lemmen C (2002) Active Learning in the Drug Discovery Process
In: Advances in Neural Information Processing Systems 14, (Ed) Dietterich, T.G. , S. Becker, Z. Ghahramani, Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), MIT Press, Cambridge, MA, USA, 1449-1456.
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Rätsch G , Mika S and Warmuth MK (2002) On the Convergence of Leveraging
In: Advances in Neural Information Processing Systems 14, (Ed) Dietterich, T.G. , S. Becker, Z. Ghahramani, Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), MIT Press, Cambridge, MA, USA, 487-494.
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Rätsch G and Warmuth MK (2002) Maximizing the Margin with Boosting
(Ed) Kivinen, J.; Sloan, R. H., Proceedings of the Annual Conference on Computational Learning Theory, 334-350.
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Sonnenburg S , Rätsch G , Jagota A and Müller K-R (2002) New methods for Splice Site recognition
Proceedings of the International Conference on Artificial Neural Networks.
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Tsuda K , Rätsch G , Mika S and Müller K-R (2001) Learning to predict the leave-one-out error of kernel based classifiers
(Ed) H. Bischof G. Dorffner and K. Hornik, International Conference on Artificial Neural Networks, ICANN'01, 331-338.
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Mika S , Rätsch G , Weston J , Schölkopf B , Smola AJ and Müller K-R (2000) Invariant feature extraction and classification in kernel spaces
In: Advances in neural information processing systems 12, (Ed) SA Solla, TK Leen and K-R Müller, 13th Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 526-532.
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Rätsch G , Schölkopf B , Smola AJ , Müller K-R , Onoda T and Mika S (2000) v-Arc: Ensemble Learning in the Presence of Outliers
In: Advances in Neural Information Processing Systems 12, (Ed) SA Solla, TK Leen and K-R Müller, 13th Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 561-567.
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gunnar.raetsch
