ARCHIVE Snapshot of the Rätsch lab website (Tübingen, then New York) as of February 2016: preserved, not maintained. The group today: bmi.inf.ethz.ch
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Bibliography

References to publications, sorted by year and author.
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2003 Meir, R and Rätsch, G (2003).
An Introduction to Boosting and Leveraging
In: Advanced Lectures on Machine Learning, ed. by S. Mendelson and A. Smola, vol. 2006, pp. 118-183, Springer Verlag. Lecture Notes in Computer Science.
Online Access Printable file

Mendelson, S and Philips, P (2003).
Random Subclass Bounds
In: Proceedings of the 16th Annual Conference on Learning Theory, COLT 2003, ed. by B. Schölkopf and M. Warmuth, pp. 329-343, Springer. LNCS 2777.

Mika, S, Rätsch, G, Weston, J, Schölkopf, B, Smola, A, and Müller, K (2003).
Constructing Descriptive and Discriminative Non-Linear Features: Rayleigh Coefficients in Kernel Feature Space
IEEE PAMI (http://www.computer.org/tpami, 25(5):623-633.
Online Access

Ong, CS and Smola, AJ (2003).
Machine Learning with Hyperkernels
In: International Conference of Machine Learning, pp. 568–575.

Ong, CS, Smola, AJ, and Williamson, RC (2003).
Hyperkernels
In: Advances in Neural Information Processing Systems 15, pp. 495–502.

Rätsch, G, Smola, AJ, and Mika, S (2003).
Adapting Codes and Embeddings for Polychotomies
In: Advances in Neural information processing systems (http://www-2.cs.cmu.edu/Web/Groups/NIPS/NIPS2002/nips-papers.html), MIT Press.

Rätsch, G (2003).
Robust Multi-Class Boosting
In: EuroSpeech, pp. 997-1000, IEEE, Geneva.
Online Access

Shin, H and Cho, S (2003).
Fast Pattern Selection Algorithm for Support Vector Classifiers: Time Complexity Analysis
Lecture Notes in Computer Science, 2690:1008-1015.

Shin, H and Cho, S (2003).
Fast Pattern Selection Algorithm for Support Vector Classifiers
Lecture Notes in Artificial Intelligence, 2637:376-387.

Shin, H and Cho, S (2003).
How Many Neighbors To Consider in Pattern Pre-selection for Support Vector Classifiers?
Proc. of INNS-IEEE International Joint Conference on Neural Networks (IJCNN):565-570.

Shin, H and Cho, S (2003).
How to Deal with Large Dataset, Class Imbalance and Binary Output in SVM based Response Model
Proc. of the Korean Data Mining Society Conference:93-107.

Shin, H and Cho, S (2003).
Time Complexity Analysis of Fast Pattern Selection Algorithm for SVM
Proc. of the Korean Data Mining Society Conference:221-231.

Tsuda, K and Rätsch, G (2003).
Image Reconstruction by Linear Programming
Max-Planck Institute for Biological Cybernetics, Tübingen.
Online Access

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 (http://pubs.acs.org/journals/jcisd8), 43(2):667-673.
Online Access

2002 Kellner, A, Souvignier, B, Portele, T, and Philips, P (2002).
Dialog System
Miscellaneous publication, US patent application 20020065651.

Rätsch, G (2002).
Robustes Boosting durch konvexe Optimierung
In: Ausgezeichnete Informatikdissertationen 2001, ed. by D. Wagner et al., pp. 125-136, Bonner Köllen.
Online Access

Rätsch, G, Mika, S, Schölkopf, B, and Müller, K (2002).
Constructing Boosting Algorithms from SVMs: an Application to One-Class Classification
IEEE TPAMI, 24(9).

Shin, H and Cho, S (2002).
Pattern Selection Algorithm for Support Vector Classifiers
Lecture Notes in Computer Science, 2412:469-474.

Shin, H and Cho, S (2002).
Pattern Selection Using the Bias and Variance of Ensemble
Journal of the Korean Institute of Industrial Engineers, 28(1):112-127.

Shin, H and Cho, S (2002).
Decision Boundary Pattern Selection for Support Vector Machines
Proc. of the Korean Data Mining Society Conference.

Shin, H and Cho, S (2002).
k-NN based Pattern Selection for Support Vector Classifiers
Proc. of the Korean Operations Research and Management Science Society Conference:645-651.

Sonnenburg, S, Rätsch, G, Jagota, A, and Müller, KR (2002).
New Methods for Splice Site Recognition
In: ICANN '02: Proceedings of the International Conference on Artificial Neural Networks, pp. 329 - 336, Springer-Verlag.
Online Access Printable file

Tsuda, K, Kawanabe, M, Rätsch, G, Sonnenburg, S, and Müller, KR (2002).
A New Discriminative Kernel from Probabilistic Models
Neural Computation, 14:2397-2414.
Online Access

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 (http://www-2.cs.cmu.edu/Web/Groups/NIPS/NIPS2001/nips.html), ed. by T. G. Dietterich and S. Becker and Z. Ghahramani.

2001 Kellner, A and Philips, P (2001).
Verfahren zur stochastischen Kombination mehrerer Modalitaeten in einem Dialogsystem (Synchronous Combination of Multi-Modal Inputs)
Miscellaneous publication, Philips Research Laboratories, Erfindungsmeldung ID 201790.

 
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