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Machine Learning

Conference Publications

1991

Erwin, E., Obermayer, K. and Schulten, K. (1991). Convergence Properties of Self-organizing Maps. Artificial Neural Networks I. North Holland, 409 – 414.

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1992

Obermayer, K. (1992). Neural Pattern Formation and Self-Organizing Maps. Annales de Groupe CARNAC 5, 91 – 104.


1997

Südholt, M., Piepenbrock, C., Obermayer, K. and Pepper, P. (1997). Solving Large Systems of Differential Equations using Convolutions by Transformation. IFIP Working Conference on Algorithmic Languages and Calculi, Strasbourg. Chapman \\& Hall, (1 – 27).

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Burger, M., Graepel, T. and Obermayer, K. (1997). Phase Transitions in Soft Topographic Vector Quantization. Artificial Neural Networks - ICANN 97. Springer-Verlag, 619 – 624.

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Graepel, T., Burger, M. and Obermayer, K. (1997). Deterministic Annealing for Topographic Vector Quantization and Self-Organizing Maps. Proceedings of the Workshop on Self-Organizing Maps - WSOM 97, 345 – 350.

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1998

Burger, M. a. G. T. and Obermayer, K. (1998). An Annealed Self-Organizing Map for Source Channel Coding. Advances in Neural Information Processing Systems 10. MIT Press, 430 – 436.

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Graepel, T. and Obermayer, K. (1998). Fuzzy Topographic Kernel Clustering. Proceedings of the 5th GI Workshop Fuzzy Neuro Systems, 90 – 97.

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1999

Schöner, H., Stetter, M., Schiessl, I., Mayhew, J., Lund, J., McLoughlin, N. and Obermayer, K. (1999). Blind Separation of Noisy Mixtures by Iterative Decorrelation.. Proceedings. The Learning Workshop, Snowbird, USA, (1 – 2).

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Graepel, T., Herbrich, R., Bollmann-Sdorra, P. and Obermayer, K. (1999). Classification on Pairwise Proximity Data. Advances in Neural Information Processing Systems 11. MIT Press, 438 – 444.

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Graepel, T., Herbrich, R. and Obermayer, K. (1999). Bayesian transductive classification by maximizing volume in version space. Proceedings of Learning 1999 Conference


Graepel, T., Herbrich, R., Schoelkopf, B., Smola, A., Bartlett, P., Mueller, K., Obermayer, K. and Williamson, R. (1999). Classification on Proximity Data with LP-Machines. 9th International Conference on Artificial Neural Networks - ICANN99. IEEE, 304 – 309.

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Hasenjäger, M., Ritter, H. and Obermayer, K. (1999). Active Data Selection for Fuzzy Topographic Mapping of Proximities. Fuzzy-Neuro Systems 1999 - Computational Intelligence, 93–104.

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Hasenjäger, M., Ritter, H. and Obermayer, K. (1999). Active Topographic Mapping of Proximities. 9th International Conference on Artificial Neural Networks - ICANN99. IEEE, 952 – 957.

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Herbrich, R., Graepel, T. and Obermayer, K. (1999). Support Vector Learning for Ordinal Regression. 9th International Conference on Artificial Neural Networks - ICANN99. IEEE, 97 – 102.

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2000

Seo, S., Wallat, M., Graepel, T. and Obermayer, K. (2000). Gaussian Process Regression: Active Data Selection and Test Point Rejection. Neural Networks - IJCNN 2000. IEEE, 241 – 246.

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Graepel, T., Herbrich, R. and Obermayer, K. (2000). Bayesian Transduction. Advances in Neural Information Processing Systems 12. MIT Press, 456 – 462.

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Hasenjäger, M., Ritter, H. and Obermayer, K. (2000). Active Data Selection for Topographic Pairwise Clustering. Classification, Automation, and New Media. Program of the 24th Annual Conference of the German Classification Society (GfKl), 80.

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2003

Hochreiter, S., Mozer, M. and Obermayer, K. (2003). Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. Advances in Neural Information Processing Systems 15. MIT Press, 561 – 568.

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Hochreiter, S. and Obermayer, K. (2003). Feature Selection and Classification on Matrix Data: From Large Margins To Small Covering Numbers. Advances in Neural Information Processing Systems 15. MIT Press, 913 – 920.

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Cuadros-Vargas, E., Romero, R. and Obermayer, K. (2003). Speeding up Algorithms of the SOM Family for Large and High Dimensional Databases. Proceedings WSOM, 167 – 172.

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