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2007

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


Martinez, E., Adiloglu, K., Annies, R., Purwins, H. and Obermayer, K. (2007). Representation of Everyday Sounds for Classification of their Perceived Function. Proc. Audio Mostly Conference, 90 – 95.,


Neubauer, N., Scheel, C., Albayrak, A. and Obermayer, K. (2007). Distance Measures in Query Space: How Strongly to Use Feedback from Past Queries. Proceedings of the IEEE Conference on Web Intelligence 2007. IEEE, 607 – 613.,10.1109/WI.2007.65


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).,


Schummers, J., Cronin, B., Wimmer, K., Stimberg, M., Martin, R., Obermayer, K., Koerding, K. and Sur, M. (2007). Dynamics of Orientation Tuning in Cat V1 Neurons Depend on Location within Layers and Orientation Maps. Frontiers in Neuroscience, 1, 145 – 159.


Annies, R., Martinez, E., Adiloglu, K., Purwins, H. and Obermayer, K. (2007). Classification Schemes for Step Sounds Based on Gammatone-Filters. Proceedings of the IEEE Conference on Web Intelligence 2007,


Adiloglu, K. and Obermayer, K. (2007). Topological Features of the Two-Voice Inventions. Communications in Computer and Information Science. Springer Berlin Heidelberg, 67 – 73.,10.1007/978-3-642-04579-0_7


Stimberg, M., Hoch, T. and Obermayer, K. (2007). The Effect of Background Noise on the Precision of Pulse Packet Propagation in Feed-Forward Networks. Neurocomputing, 70, 1824 – 1828.


Young, J., Waleszczyk, W., Wang, C., Calford, M., Dreher, B. and Obermayer, K. (2007). Cortical Reorganization Consistent with Spike Timing- but not Correlation-Dependent Plasticity. Nat. Neurosci., 10, 887 – 889.


Gallinat, J., Obermayer, K. and Heinz, A. (2007). Systems Biology of the Dysfunctional Brain: Schizophrenia. Pharmacopsychiatry, 40, 40 – 44.


Grünewälder, S. and Obermayer, K. (2007). Optimality of LSTD and its Relation to MC. Neural Networks, IJCNN 2007, 338 – 343.,


2008

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


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


Lohoff, F., Lautenschlager, M., Mohr, J., Ferraro, T., Sander, T. and Gallinat, J. (2008). Association Between Variation in the Vesicular Monoamine Transporter 1 Gene on Chromosome 8p and Anxiety-Related Personality Traits. Neuroscience Letters, 434, 41 – 45.


Mohr, J., Jain, B. and Obermayer, K. (2008). Molecule Kernels: A Descriptor- and Alignment-Free QSAR Approach. Journal of Chemical Information and Modeling, 48, 1868 – 1881.


Mohr, J., Seo, S. and Obermayer, K. (2008). Automated Microarray Classification Based on P-SVM Gene Selection. Proceedings of the ICMLA '08: The Seventh International Conference on Machine Learning and Applications. IEEE, 503 – 507.,10.1109/ICMLA.2008.75


Mohr, J., Seo, S., Puls, I., Heinz, A. and Obermayer, K. (2008). Target Selection: A New Learning Paradigm and its Application to Genetic Association Studies. Proceedings of the ICMLA '08: The Seventh International Conference on Machine Learning and Applications. IEEE, 182 – 187.,10.1109/ICMLA.2008.58


Ochab, B., Neubauer, N. and Obermayer, K. (2008). Personalized Recommendations for the Web 3D. Lecture Notes in Computer Science. Springer Verlag, 374 – 377.,http://dx.doi.org/10.1007/978-3-540-70987-9_57


Puls, I., Mohr, J., Wrase, J., Priller, J., Behr, J., Kitzrow, W., Makris, N., Breiter, H., Obermayer, K. and Heinz, A. (2008). Synergistic Effects of the Dopaminergic and Glutamatergic System on Hippocampal Volume in Alcohol-Dependent Patients. Biological Psychology, 79, 126 - 136.


Purwins, H., Blankertz, B. and Obermayer, K. (2008). Toroidal Models in Tonal Theory. Tonal Theory for the Digital Age - Computing in Musicology. Stanford University, 73 – 98.,


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