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Dr. Gunnar Rätsch

Raum Nummer: FML 0.06a
Fax: 07071 601 801

 

Bild von Rätsch, Gunnar, Dr.

Gunnar Rätsch

Position: Wissenschaftler  Abteilung: 

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Beiträge zu Tagungsbänden (33):

Mika S, Rätsch G, Weston J, Schölkopf B, Smola AJ und Müller K-R (Juni-2000) Invariant feature extraction and classification in kernel spaces In: Advances in neural information processing systems 12, , Thirteenth 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 und Mika S (Juni-2000) v-Arc: Ensemble Learning in the Presence of Outliers In: Advances in Neural Information Processing Systems 12, , Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 561-567.
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Rätsch G, Schölkopf B, Smola AJ, Mika S, Onoda T und Müller K-R (April-2000) Robust Ensemble Learning for Data Mining In: Knowledge Discovery and Data Mining: Current Issues and New Applications, , Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000), Springer, Berlin, Germany, 341-344, Series: Lecture Notes in Artificial Intelligence ; 1805.
Rätsch G, Schölkopf B, Smola AJ, Mika S, Onoda T und Müller K-R (2000) Robust ensemble learning In: Advances in Large Margin Classifiers, , NIPS 1998 Workshop “Advances in Large Margin Classifiers”, MIT Press, Cambridge, MA, USA, 207-220, Series: Neural Information Processing Series.
Smola AJ, Schölkopf B und Rätsch G (September-1999) Linear programs for automatic accuracy control in regression, Ninth International Conference on Artificial Neural Networks (ICANN 99), Institute of Electrical Engineers, London, UK, 575-580, Series: Conference Publication of the Institution of Electrical Engineers ; 470.
Mika S, Rätsch G, Weston J, Schölkopf B und Müller K-R (August-1999) Fisher discriminant analysis with kernels In: Neural networks for signal processing IX, , 1999 IEEE Signal Processing Society Workshop, IEEE, Piscataway, NJ, USA, 41-48.
Mika S, Schölkopf B, Smola AJ, Müller K-R, Scholz M und Rätsch G (Juni-1999) Kernel PCA and De-noising in feature spaces In: Advances in Neural Information Processing Systems 11, , Twelfth Annual Conference on Neural Information Processing Systems (NIPS 1998), MIT Press, Cambridge, MA, USA, 536-542.
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Rätsch G, Onoda T und Müller KR (Juni-1999) Regularizing AdaBoost In: Advances in Neural Information Processing Systems 11, , Twelfth Annual Conference on Neural Information Processing Systems (NIPS 1998), MIT Press, Cambridge, MA, USA, 564-570.
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Müller K-R, Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J und Vapnik V (1999) Using support vector machines for time series prediction In: Advances in kernel methods: support vector learning, , Eleventh Annual Conference on Neural Information Processing (NIPS 1997), MIT Press, Cambridge, MA, USA, 243-253.
Schölkopf B, Mika S, Smola AJ, Rätsch G und Müller K-R (September-1998) Kernel PCA pattern reconstruction via approximate pre-images In: ICANN 98, , 8th International Conference on Artificial Neural Networks, Springer, Berlin, Germany, 8th International Conference on Artificial Neural Networks, 147-152, Series: Perspectives in Neural Computing.
Müller K-R, Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J und Vapnik V (Oktober-1997) Predicting time series with support vector machines In: Artificial Neural Networks - ICANN '97, , 7th International Conference on Artificial Neural Networks, Springer, Berlin, Germany, 999-1004, Series: Lecture Notes in Computer Science ; 1327.
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Beiträge zu Büchern (2):

Müller K-R, Mika S, Rätsch G, Tsuda K und Schölkopf B: An Introduction to Kernel-Based Learning Algorithms, 95-134. In: Handbook of neural network signal processing, (Ed) Y.H. Hu, CRC Press, Boca Raton, FL, USA, (2002).
Rätsch G: Robustes Boosting durch konvexe Optimierung, 125-136. (Ed) D. Wagner, Bonner Köllen, (2002).

Technische Berichte (2):

Zien A, Raetsch G und Ong CS: Towards the Inference of Graphs on Ordered Vertexes, 150, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (August-2006).
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Tsuda K und Rätsch G: Image Reconstruction by Linear Programming, 118, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (Oktober-2003).
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Poster (8):

Drewe P, Stegle O, Bohnert R, Borgwardt KM und Rätsch G (Juli-2010): Detecting differential RNA-transcript expression, 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2010), Boston, MA, USA, F1000Posters, 2010(1) 269.
Stegle O, Drewe P, Bohnert R, Borgwardt K und Rätsch G (Juni-2010): Detecting Differential Transcript Expression from RNA-SEQ Experiments, 3rd Berlin Summer Meeting: Computational & Experimental Molecular Biology Meet, Berlin, Germany.
Rätsch G, Clark R, Schweikert G, Toomajian C, Ossowski S, Zeller G, Shinn P, Warthman N, Hu T, Fu G, Hinds D, Cheng H, Frazer K, Huson D, Schölkopf B, Nordborg M, Ecker J, Weigel D, Schneeberger K und Bohlen A (Juli-2008): Discovering Common Sequence Variation in Arabidopsis thaliana, 16th Annual International Conference Intelligent Systems for Molecular Biology (ISMB 2008), Toronto, Canada.
De Bona F, Ong C-S, Zien A und Rätsch G (Juli-2007): RNA secondary structure prediction using large margin methods, 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2007) and 6th European Conference on Computational Biology (ECCB 2007), Wien, Austria.
Zeller G, Schweikert G, Clark R, Ossowski S, Warthman N, Shinn P, Frazer K, Ecker J, Huson D, Weigel D, Schölkopf B und Rätsch G (August-2006): Machine Learning Algorithms for Polymorphism Detection, 14th International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Fortaleza, Brazil.
Rätsch G, Sonnenburg S, Srinivasan J, Müller K-R, Sommer R und Schölkopf B (August-2006): Splice Form Prediction using Machine Learning, 14th International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Fortaleza, Brazil.
Clark R, Ossowski S, Schweikert G, Zeller G, Shinn P, Raetsch G, Warthmann N, Fu G, Hinds D, Cheng H, Frazer K, Toomajian C, Hu T, Huson D, Schoelkopf B, Nordborg M, Ecker J und Weigel D (April-2006): An Inventory of Common Sequence Polymorphisms for Arabidopsis, 17th International Conference on Arabidopsis Research (ICAR 2006), Madison, WI, USA.
Zien A, Rätsch G, Mika S, Schölkopf B, Lemmen C, Smola A, Lengauer T und Müller K-R (Oktober-1999): Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites, German Conference on Bioinformatics (GCB '99), Heidelberg, Germany.

Abschlussarbeiten (1):

Rätsch G: Robust Boosting via Convex Optimization, (Oktober-2001). PhD thesis

Vorträge (13):

Rätsch G (Juli-11-2012) Invited Lecture: An Introduction to Kernel Methods for Classification, Regression and the Analysis of Structured Data, Machine Learning Summer School 2012, Santa Cruz, CA, USA.
Rätsch G (Dezember-12-2009) Keynote Lecture: Transfer Learning Methods and Applications in Computational Biology, NIPS 2009 Workshop on Transfer Learning for Structured Data (TLSD-09), Whistler, BC, Canada.
Schultheiss SJ, Busch W, Lohmann J, Kohlbacher O und Rätsch G (Dezember-12-2008) Invited Lecture: KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences, NIPS 2008 Workshop on Machine Learning in Computational Biology, Whistler, BC, Canada.
Schweikert G, Zeller G, Zien A, Behr J, Sonnenburg S, Philips P, Ong CS und Rätsch G (Juli-25-2008) Abstract Talk: mGene: A Novel Discriminative Gene Finder, 2008 Topics Meeting: Worm Genomics and Systems Biology, Cambridge, USA.
Schweikert G, Zeller G, Behr J, Zien A, Ong CS, De Bona F, Sonnenburg S, Philips P, Raetsch G und Widmer C (Juli-18-2008) Abstract Talk: mGene: A Novel Discriminative Gene Finding System, 4th ISCB Student Council Symposium at ISMB 2008, Toronto, Canada 20.
Schweikert G, Zeller G, Weigel D, Schölkopf B und Rätsch G (Dezember-8-2007) Abstract Talk: Machine Learning Algorithms for Polymorphism Detection, NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007), Whistler, BC, Canada.
Sonnenburg S, Zien A, Philips P und Rätsch G (Dezember-8-2007) Abstract Talk: Positional Oligomer Importance Matrices, NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007), Whistler, BC, Canada.
Ong CS, Hartmann L, Bohnert R, Krüger N, Bohlen A und Rätsch G (Juli-20-2007) Abstract Talk: Bootstrapping the alternative splicing annotation of newly sequenced genomes, Alternative Splicing: Special Interest Group Meeting (AS-SIG) at ISMB 2007, Wien, Austria 33-35.
Schweikert G, Zeller G, Zien A, Ong CS, de Bona F, Sonnenburg S, Phillips P und Rätsch G (Dezember-8-2006) Abstract Talk: Ab-initio gene finding using machine learning, NIPS 2006 Workshop on New Problems and Methods in Computational Biology (MLCB 2006), Whistler, BC, Canada.
Rätsch G und Ong CS (September-19-2006) Invited Lecture: Kernel Methods for Predictive Sequence Analysis, German Conference on Bioinformatics (GCB 2006), Tübingen, Germany.
Schweikert G, Zeller G, Clark R, Ossowski S, Warthmann N, Shinn P, Frazer K, Ecker J, Huson D, Weigel D, Schölkopf B und Rätsch G (August-2006): Machine Learning Algorithms for Polymorphism Detection, 2nd ISCB Student Council Symposium at ISMB 2006, Fortaleza, Brazil.
Rätsch G, Sonnenburg S, Ong CS und Schölkopf B (Dezember-9-2005) Invited Lecture: Accurate prediction of alternative splicing events, NIPS Workshop on Computational Biology and the Analysis of Heterogeneous Data (MLCB 2005), Whistler, BC, Canada.
Rätsch G und Tsuda K (August-2-2004) Abstract Talk: The v-Trick for Image Reconstruction, First Mathematical Programming Society International Conference on Continuous Optimization (ICCOPT I), Troy, NY, USA 55.
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Last updated: Montag, 22.05.2017