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 | 2013 | |
|---|---|---|
| i2 |      | Tobias Glasmachers, Ürün Dogan: Accelerated Linear SVM Training with Adaptive Variable Selection Frequencies. CoRR abs/1302.5608 (2013) |
| 2012 | ||
| j8 | | Tobias Glasmachers, Jan Koutník, Jürgen Schmidhuber: Kernel representations for evolving continuous functions. Evolutionary Intelligence 5(3): 171-187 (2012) |
| c13 | | Ürün Dogan, Tobias Glasmachers, Christian Igel: A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes. ECML/PKDD (1) 2012: 122-129 |
| c12 | | Tobias Glasmachers: Convergence of the IGO-Flow of Isotropic Gaussian Distributions on Convex Quadratic Problems. PPSN (1) 2012: 1-10 |
| 2011 | ||
| c11 | | Tom Schaul, Leo Pape, Tobias Glasmachers, Vincent Graziano, Jürgen Schmidhuber: Coherence Progress: A Measure of Interestingness Based on Fixed Compressors. AGI 2011: 21-30 |
| c10 | | |
| c9 | | Giuseppe Cuccu, Faustino J. Gomez, Tobias Glasmachers: Novelty-based restarts for evolution strategies. IEEE Congress on Evolutionary Computation 2011: 158-163 |
| c8 | | Tom Schaul, Tobias Glasmachers, Jürgen Schmidhuber: High dimensions and heavy tails for natural evolution strategies. GECCO 2011: 845-852 |
| i1 | | Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jürgen Schmidhuber: Natural Evolution Strategies. CoRR abs/1106.4487 (2011) |
| 2010 | ||
| j7 | | Tobias Glasmachers, Christian Igel: Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. IEEE Trans. Pattern Anal. Mach. Intell. 32(8): 1522-1528 (2010) |
| c7 | | Tobias Glasmachers, Tom Schaul, Yi Sun, Daan Wierstra, Jürgen Schmidhuber: Exponential natural evolution strategies. GECCO 2010: 393-400 |
| c6 | | Tobias Glasmachers: Universal Consistency of Multi-Class Support Vector Classification. NIPS 2010: 739-747 |
| c5 | | Tobias Glasmachers, Tom Schaul, Jürgen Schmidhuber: A Natural Evolution Strategy for Multi-objective Optimization. PPSN (1) 2010: 627-636 |
| 2008 | ||
| b1 | | Tobias Glasmachers: Gradient based optimization of support vector machines. Ruhr University Bochum 2008 |
| j6 | | Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers: Shark. Journal of Machine Learning Research 9: 993-996 (2008) |
| j5 | | Tobias Glasmachers, Christian Igel: Second-Order SMO Improves SVM Online and Active Learning. Neural Computation 20(2): 374-382 (2008) |
| c4 | | Tobias Glasmachers: On related violating pairs for working set selection in SMO algorithms. ESANN 2008: 475-480 |
| c3 | | Tobias Glasmachers, Christian Igel: Uncertainty Handling in Model Selection for Support Vector Machines. PPSN 2008: 185-194 |
| 2007 | ||
| j4 | | Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel: Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts. Int. J. Neural Syst. 17(5): 369-381 (2007) |
| j3 | | Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke: Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE/ACM Trans. Comput. Biology Bioinform. 4(2): 216-226 (2007) |
| 2006 | ||
| j2 | | Tobias Glasmachers, Christian Igel: Maximum-Gain Working Set Selection for SVMs. Journal of Machine Learning Research 7: 1437-1466 (2006) |
| c2 | | Tobias Glasmachers: Degeneracy in model selection for SVMs with radial Gaussian kernel. ESANN 2006: 587-592 |
| c1 | | Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel: Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. ICANN (2) 2006: 827-836 |
| 2005 | ||
| j1 | | Tobias Glasmachers, Christian Igel: Gradient-Based Adaptation of General Gaussian Kernels. Neural Computation 17(10): 2099-2105 (2005) |
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