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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2001 Müller, K, Mika, S, Rätsch, G, Tsuda, K, and Schölkopf, B (2001).
An Introduction to Kernel-based Learning Algorithms
IEEE Neural Networks, 12(2):181-201.
Online Access

Mika, S, Rätsch, G, and Müller, K (2001).
A mathematical programming approach to the Kernel Fisher algorithm
In: Proc. NIPS 13 (http://www.cs.cmu.edu/afs/cs/project/cnbc/nips/NIPS.html), ed. by T. K. Leen and T. G. Dietterich and V. Tresp, pp. 591-597, MIT Press.

Onoda, T, Rätsch, G, and Müller, KR (2001).
An Arcing algorithm with an intuitive learning control parameter
Journal of the Japanese Society fo AI (http://www.jssst.or.jp/jsai/journal/index/index-e.html), 16(5C):417-426.
Online Access

Rätsch, G (2001).
Robust Boosting via Convex Optimization
PhD thesis, University of Potsdam, Mathematisch-Naturwissenschaftliche Fakultät, Universität Potsdam.
Printable file

Rätsch, G and Warmuth, MK (2001).
Marginal Boosting
Royal Holloway College, NeuroCOLT2, Technical Report (97), London.
Online Access

Rätsch, G, Mika, S, and Warmuth, MK (2001).
On the Convergence of Leveraging
Royal Holloway College, NeuroCOLT2, Technical Report (98), London.
Online Access

Shin, H and Cho, S (2001).
Pattern Selection for `Regression' using the Bias and Variance of Ensemble Network
Proc. of the Korean Institute of Industrial Engineers Conference (KIIE).

Shin, H and Sungzoon (2001).
Pattern Selection for `Classification' using the Bias and Variance of Ensemble Neural Network
Proc. of the 28th Korea Information Science Society Conference:307-309.

Tsuda, K, Rätsch, G, Mika, S, and Müller, K (2001).
Learning To Predict the Leave-one-out Error of Kernel based classifiers
In: Proc. ICANN'01.

Wong, FW, Supian, AS, Ismail, AF, Lai, WK, and Ong, CS (2001).
Enhanced User Authentication through Typing Biometrics with Artificial Neural Networks and K-Nearest Neighbor Algorithm
In: Proceedings of the 35th Asilomar Conference on Signals, Systems & Computers.

2000 Kellner, A, Martin, S, Philips, P, Portele, T, and Souvignier, B (2000).
Conversational User Interfaces for Consumer Electronics
In: Philips User Interface Conference 2000 (UI2000), Eindhoven, Netherlands.

Kohlmorgen, J, Lemm, S, Rätsch, G, and Müller, K (2000).
Analysis of Nonstationary Time Series by Mixtures of Self-Organizing Predictors
In: Proc.NNSP'2000 (http://eivind.imm.dtu.dk/nnsp2000/), pp. 85-94, Sydney.

Mika, S, Rätsch, G, Weston, J, Schölkopf, B, Smola, AJ, and Müller, K (2000).
Learning Discriminative and Invariant Nonlinear Features
Unpublished.

Mika, S, Rätsch, G, Weston, J, Schölkopf, B, Smola, AJ, and Müller, K (2000).
Invariant Feature Extraction and Classification in Kernel Spaces
In: Proc. NIPS 12 (http://www.cs.cmu.edu//Web/Groups/NIPS/NIPS99/nips99.html), ed. by S. A. Solla and T. K. Leen and K.-R. Müller, pp. 526-532, MIT Press.

Ong, CS (2000).
Knowledge Discovery in Databases: An Information Retrieval Perspective
Malaysian Journal of Computer Science, 13(2).

Ong, CS and Lai, WK (2000).
Enhanced Password Authentication Through Typing Biometrics with K-Means Clustering Algorithm
In: World Automation Congress.

Ong, CS, Wong, F, and Lai, WK (2000).
A High Resolution and Accurate Pentium Based Timer
In: National Real Time Technology and Applications Symposium, Malaysia.

Onoda, T and Rätsch, G (2000).
Trends in Boosting Research and Applications
Central Research Institute of the Electric Power Industry, CRIEPI, Tokyo.

Onoda, T, Rätsch, G, and Müller, K (2000).
An asymptotical Analysis and Improvement of AdaBoost in the binary classification case
Journal of the Japanese Society for AI , 15(2):287-296.

Onoda, T, Rätsch, G, and Müller, K (2000).
A Non-Intrusive Monitoring System for Household Electric Appliances with Inverters
In: Proc. of NC'2000, Berlin.

Rätsch, G, Demiriz, A, and Bennett, K (2000).
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Royal Holloway College, NeuroCOLT2, Technical Report , London.

Rätsch, G, Schölkopf, B, Mika, S, and Müller, K (2000).
SVM and Boosting: One Class
GMD FIRST, Technical Report (119), Berlin.

Rätsch, G, Schölkopf, B, Smola, AJ, Mika, S, Onoda, T, and Müller, K (2000).
Robust Ensemble Learning
In: Proc. of the NIPS*Workshop on Large Margin Classifiers: Advances in Large Margin Classifiers, ed. by A. J. Smola, P. L. Bartlett, B. Schölkopf and D. Schuurmans, pp. 207-219, MIT Press, Cambridge, MA.

Rätsch, G, Schölkopf, B, Smola, AJ, Mika, S, Onoda, T, and Müller, K (2000).
Robust Ensemble Learning for Data Mining
In: Proc. of PAKDD'2000. Lecture Notes in Artificial Intelligence, Springer-Verlag.

Rätsch, G, Warmuth, M, Mika, S, Onoda, T, Lemm, S, and Müller, K (2000).
Barrier Boosting
In: Proc. COLT'00, ed. by Morgan Kaufmann, pp. 170-179, Palo Alto.

 
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