Publikationen von G Rätsch

Sonnenburg, S.; Rätsch, G.; Schäfer, C.; Schölkopf, B.: Large Scale Multiple Kernel Learning. The Journal of Machine Learning Research 7, S. 1531 - 1565 (2006)

Rätsch, G.; Warmuth, M.: Efficient Margin Maximizing with Boosting. Journal of Machine Learning Research 6, S. 2131 - 2152 (2005)

Müller, K.-R.; Rätsch, G.; Sonnenburg, S.; Mika, S.; Grimm, M.; Heinrich, N.: Classifying "drug-likeness" with kernel-based learning methods. Journal of Chemical Information and Modeling 45 (2), S. 249 - 253 (2005)

Rätsch, G.: Intelligente Algorithmen zur Analyse zellulärer Spleißmechanismen [Intelligent Algorithms for the Analysis of Cellular Splicing Mechanisms]. Jahrbuch der Max-Planck-Gesellschaft 2005 (2005)

Tsuda, K.; Kawanabe, M.; Rätsch, G.; Sonnenburg, S.; Müller, K.: A New Discriminative Kernel from Probabilistic Models. Neural computation 14 (10), S. 2397 - 2414 (2002)

Sonnenburg, S.; Rieck, K.; Rätsch, G.: Large Scale Learning with String Kernels. In: Large-scale kernel machines, 4, S. 73 - 103 (Hg. Bottou, L.). MIT Press (2007)

Rätsch, G.; Sonnenburg, S.: Accurate Splice Site Detection for Caenorhabditis elegans. In: Kernel Methods in Computational Biology, S. 277 - 298 (Hg. Schölkopf, B.; Tsuda, K.; Vert, J.-P.). MIT Press, Cambridge, MA, USA (2004)

Goldenberg, A.; Hertz, T.; Leslie, C.; Qi, Y.; Rätsch, G.; Vert, J.-P. (Hg.): NIPS 2011 Workshop Machine Learning in Computational Biology. NIPS 2011 Workshop Machine Learning in Computational Biology, Melia Sierra Nevada, Spain, 17. Dezember 2011. (2011)

Machine Learning in Computational Biology. NIPS 2010 Workshop: Machine Learning in Computational Biology (MLCB 2010), Whistler, BC, Canada, 10. Dezember 2010 - 11. Dezember 2010. (2010)

Chechik, G.; Leslie, C.; Noble, W.; Rätsch, G.; Morris, Q.; Tsuda, K. (Hg.): NIPS Workshop on New Problems and Methods in Computational Biology (BMC Bioinformatics, 8). NIPS Workshop on New Problems and Methods in Computational Biology 2006, Whistler, Canada, 08. Dezember 2006. (2007)

Chechik, G.; Leslie, C.; Rätsch, G.; Tsuda, K. (Hg.): NIPS Workshop on New Problems and Methods in Computational Biology (BMC Bioinformatics, 7). NIPS Workshop on New Problems and Methods in Computational Biology 2004, Whistler, Canada, 08. Dezember 2004. (2006)

Widmer, C.; Kloft, M.; Görnitz, N.; Rätsch, G.: Efficient Training of Graph-Regularized Multitask SVMs. In: Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2012, S. 633 - 647 (Hg. Flach, P.; De Bie, T.; Cristianini, N.). European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2012), Bristol, UK, 24. September 2012 - 28. September 2012. Springer, Berlin, Germany (2012)

Goernitz, N.; Widmer, C.; Zeller, G.; Kahles, A.; Rätsch, G.; Sonnenburg, S.: Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation. In: Advances in Neural Information Processing Systems 24, S. 2690 - 2698 (Hg. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira , F.; Weinberger, K.). 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain, 12. Dezember 2011 - 14. Dezember 2011. Curran, Red Hook, NY, USA (2012)

Widmer, C.; Rätsch, G.: Multitask Learning in Computational Biology. In: ICML 2011 Unsupervised and Transfer Learning Workshop, S. 207 - 216 (Hg. Silver, D.; Guyon, I.; Taylor, G.; Dror, G.; Lemaire, V.). ICML 2011 Unsupervised and Transfer Learning Workshop, Bellevue, WA, USA, 02. Juli 2011. Curran, Red Hook, NY, USA (2012)

Widmer, C.; Toussaint, N.; Altun, Y.; Rätsch, G.: Multitask Multiple Kernel Learning (MT-MKL). In: NIPS 2010 Workshop: New Directions in Multiple Kernel Learning. NIPS 2010 Workshop: New Directions in Multiple Kernel Learning, Vancouver, Canada, 11. Dezember 2010. (2010)

Toussaint, N.; Widmer, C.; Kohlbacher, O.; Rätsch, G.: Exploiting physico-chemical properties in string kernels. NIPS Workshop on Machine Learning in Computational Biology (MLCB 2019), Whistler, BC, Canada, 10. Dezember 2009 - 11. Dezember 2009. BMC Bioinformatics 11 (Supplement 8), S7, (2010)

Widmer, C.; Toussaint, N.; Altun, Y.; Rätsch, G.: Inferring latent task structure for Multitask Learning by Multiple Kernel Learning. NIPS Workshop on Machine Learning in Computational Biology (MLCB 2019), Whistler, BC, Canada, 10. Dezember 2009 - 11. Dezember 2009. BMC Bioinformatics 11 (Supplement 8), S5, (2010)

Widmer, C.; Toussaint, N.; Altun, Y.; Kohlbacher, O.; Rätsch, G.: Novel Machine Learning Methods for MHC Class I Binding Prediction. In: PRIB 2010: Pattern Recognition in Bioinformatics, S. 98 - 109 (Hg. Dijkstra, T.; Tsivtsivadze, E.; Marchiori, E.; Heskes, T.). 5th IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2010), Nijmegen, The Netherlands, 22. September 2010 - 24. September 2010. Springer, Berlin, Germany (2010)

Widmer, C.; Leiva, J.; Altun, Y.; Rätsch, G.: Leveraging Sequence Classification by Taxonomy-Based Multitask Learning. In: RECOMB 2010: Research in Computational Molecular Biology, S. 522 - 534 (Hg. Berger, B.). 14th International Conference on Research in Computational Molecular Biology (RECOMB 2010), Lisboa, Portugal, 25. April 2010 - 28. April 2010. Springer, Berlin, Germany (2010)

Schweikert, G.; Widmer, C.; Schölkopf, B.; Rätsch, G.: An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis. In: Advances in neural information processing systems 21, S. 1433 - 1440 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)