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TU Berlin

Inhalt des Dokuments

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Purwins, H., Graepel, T. and Obermayer, K. (2004). Correspondence Analysis of Pitch Class, Key, and Composer. Perspectives of Mathematical and Computational Music Theory. Epos-Verlag, 432 – 454.,


Purwins, H., Normann, I. and Obermayer, K. (2005). Unendlichkeit - Konstruktion musikalischer Paradoxien. Mikrotöne und mehr: Auf György Ligetis Hamburger Pfaden. Bockel-Verlag, 39 – 80.,


Purwins, P., Blankertz, B. and Obermayer, K. (2000). A New Method for Tracking Modulations in Tonal Music in Audio Data Format. Neural Networks - IJCNN 2000. IEEE Computer Society, 270 – 275.,


Ritter, H., Obermayer, K. and Rubner, J. (1991). Self-Organizing Maps and Adaptive Filters. Physics of Neural Networks. Springer, 281 – 306.,


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).,


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).,


Schöner, H., Stetter, M., Schießl, I., Mayhew, J., Lund, J., McLoughlin, N. and Obermayer, K. (2000). Application of Blind Separation of Sources to Optical Recording of Brain Activity. Advances in Neural Information Processing Systems 12. MIT Press, 949 – 955.,


Scheel, C., Neubauer, N., Lommatzsch, A., Obermayer, K. and Albayrak, S. (2007). Efficient Query Delegation by Detecting Redundant Retrieval Strategies. SIGIR Workshop on Learning to Rank for Information Retrieval 2007, (1 – 8).,


Schießl, I., Schöner, H., Stetter, M., Dima, A. and Obermayer, K. (2000). Regularized Second Order Source Separation. Int. Workshop on Independent Component Analysis and Blind Signal Separation, 111 – 116.,


Schießl, I., Stetter, M., Mayhew, J., McLoughlin, N., Lund, J. and Obermayer, K. (2000). Blind Signal Separation from Optical Imaging Data. Mustererkennung 2000, DAGM-Symposium, 91 – 98.,


Schiessl, I., Stetter, M., Mayhew, J., Askew, S., McLoughlin, N., Levitt, J., Lund, J. and Obermayer, K. (1999). Blind Separation of Spatial Signal Patterns from Optical Imaging Records. ICA99 - International workshop on Idependent Component Analysis and Blind Source Separation, 179 – 184.,


Xie, S., Wang, L., Obermayer, K. and Zhu, F. (2016). Design of a Visual Stimulation System with LED in the Study of Spatial Selective Attention. Advances in Cognitive Neurodynamics. Springer, 461-468.,10.1007/978-981-10-0207-6_63


Böhmer, W., Springenberg, J. T., Boedecker, J., Riedmiller, M. and Obermayer, K. (2015). Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations. Künstliche Intelligenz. Springer Berlin Heidelberg, 353-362.,10.1007/s13218-015-0356-1



Schwabe, L., Adorjan, P. and Obermayer, K. (2000). A Dynamic Cortical Amplifier Model for Fast information Processing. Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on. IEEE, 431 – 435.,10.1109/IJCNN.2000.861507


Seo, S., Mohr, J., Ningfei, L., Horn, A. and Obermayer, K. (2015). Incremental pairwise clustering for large proximity matrices. 2015 International Joint Conference on Neural Networks (IJCNN), 1-8.,10.1109/IJCNN.2015.7280637


Seo, S., Mohr, J. and Obermayer, K. (2009). A New Incremental Pairwise Clustering Algorithm. Proceedings of the ICMLA -09: The Eighth International Conference on Machine Learning and Applications. IEEE, 223 – 228.,10.1109/ICMLA.2009.42


Seo, S. and Obermayer, K. (2006). Dynamic Hyperparameter Scaling Method for LVQ Algorithms. IJCNN 2006 Conference Proceedings. IEEE, 3196 – 3203.,10.1109/IJCNN.2006.247304


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.,10.1109/IJCNN.2000.861310


Seo, S., Mohr, J., Heekeren, H., Heinz, A., Eppinger, B., Li, S. and Obermayer, K. (2012). A voxel selection method for the multivariate analysis of imaging genetics data.. IJCNN. IEEE, 2884-2890.,10.1109/IJCNN.2012.6252766


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