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TU Berlin

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Machine Learning

All Publications

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Hochreiter, S. and Obermayer, K. (2005). Optimal Kernels for Unsupervised Learning. Proceedings of the International Joint Conference on Neural Networks, 1895 – 1899.,10.1109/IJCNN.2005.1556169


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.,


Hutter, F., Lücke, J. and Schmidt-Thieme, L. (2015). Beyond Manual Tuning of Hyperparameters. KI - Künstliche Intelligenz, 29, 329-337.


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Jain, B. and Obermayer, K. (2007). Theory of the Sample Mean of Structures. LNVD 2007, Learning from Non-vectorial Data, 9-16.


Jain, B. and Obermayer, K. (2011). Maximum Likelihood for Gaussians on Graphs. Graph-Based Representations in Pattern Recognition. Springer Berlin Heidelberg, 62-71.,10.1007/978-3-642-20844-7_7


Jain, B. and Obermayer, K. (2011). Generalized Learning Graph Quantization. Graph-Based Representations in Pattern Recognition. Springer Berlin Heidelberg, 122-131.,10.1007/978-3-642-20844-7_13


Jain, B. and Obermayer, K. (2010). Elkan’s k-Means Algorithm for Graphs. Advances in Soft Computing. Springer Berlin Heidelberg, 22-32.,10.1007/978-3-642-16773-7_2


Jain, B. and Obermayer, K. (2010). Consistent Estimator of Median and Mean Graph. Proceedings of the 2010 20th International Conference on Pattern Recognition. IEEE, 1032–1035.,10.1109/ICPR.2010.258


Jain, B. and Obermayer, K. (2010). Large Sample Statistics in the Domain of Graphs. Structural, Syntactic, and Statistical Pattern Recognition. Springer Berlin Heidelberg, 690 – 697.,10.1007/978-3-642-14980-1_10


Jain, B. and Obermayer, K. (2009). Algorithms for the Sample Mean of Graphs. Lecture Notes in Computer Science, 351 – 359.,


Jain, B., Srinivasan, S. D., Tissen, A. and Obermayer, K. (2010). Learning Graph Quantization. Structural, Syntactic, and Statistical Pattern Recognition. Springer Berlin Heidelberg, 109 – 118.,10.1007/978-3-642-14980-1_10


Jain, B. and Obermayer, K. (2011). Graph Quantization. J. Comput. Vision Image Understanding, 115, 946–961.


Jain, B. and Obermayer, K. (2009). Structure Spaces. Journal of Machine Learning Research, 10, 2667 – 2714.


Jain, B. and Obermayer, K. (2008). On the Sample Mean of Graphs. 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE, 993 – 1000.,10.1109/IJCNN.2008.4633920



Jain, B. and Obermayer, K. (2010). Accelerating Competetive Learning Graph Quantization. ,



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Knebel, T., Hochreiter, S. and Obermayer, K. (2008). An SMO algorithm for the Potential Support Vector Machine. Neural Comput., 20, 271 – 287.


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Laschos, V., Obermayer, K., Shen, Y. and Stannat, W. (2019). A Fenchel-Moreau-Rockafellar type theorem on the Kantorovich-Wasserstein space with applications in partially observable Markov decision processes. Journal of Mathematical Analysis and Applications


Liu, C., Xie, S., Xie, X., Duan, X., Wang, W. and Obermayer, K. (2018). Design of a Video Feedback SSVEP-BCI System for Car Control Based on the Improved MUSIC Method. Proceedings of the IEEE 6th International Winter Conference on Brain-Computer Interfaces


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