| 2009 | ||
|---|---|---|
| 47 | Thomas Voß, Nikolaus Hansen, Christian Igel: Recombination for Learning Strategy Parameters in the MO-CMA-ES. EMO 2009: 155-168 | |
| 46 | Verena Heidrich-Meisner, Christian Igel: Uncertainty handling CMA-ES for reinforcement learning. GECCO 2009: 1211-1218 | |
| 45 | Verena Heidrich-Meisner, Christian Igel: Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search. ICML 2009: 51 | |
| 2008 | ||
| 44 | Verena Heidrich-Meisner, Christian Igel: Similarities and differences between policy gradient methods and evolution strategies. ESANN 2008: 149-154 | |
| 43 | Thorsten Suttorp, Christian Igel: Approximation of Gaussian process regression models after training. ESANN 2008: 427-432 | |
| 42 | Verena Heidrich-Meisner, Christian Igel: Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. EWRL 2008: 136-150 | |
| 41 | Thomas Voß, Nicola Beume, Günter Rudolph, Christian Igel: Scalarization versus indicator-based selection in multi-objective CMA evolution strategies. IEEE Congress on Evolutionary Computation 2008: 3036-3043 | |
| 40 | Tobias Glasmachers, Christian Igel: Uncertainty Handling in Model Selection for Support Vector Machines. PPSN 2008: 185-194 | |
| 39 | Verena Heidrich-Meisner, Christian Igel: Evolution Strategies for Direct Policy Search. PPSN 2008: 428-437 | |
| 38 | Susanne Winter, Bernhard Brendel, Ioannis Pechlivanis, Kirsten Schmieder, Christian Igel: Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods. IEEE Trans. Evolutionary Computation 12(3): 284-296 (2008) | |
| 37 | Tobias Glasmachers, Christian Igel: Second-Order SMO Improves SVM Online and Active Learning. Neural Computation 20(2): 374-382 (2008) | |
| 2007 | ||
| 36 | Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller: Reinforcement learning in a nutshell. ESANN 2007: 277-288 | |
| 35 | Jan Salmen, Thorsten Suttorp, Johann Edelbrunner, Christian Igel: Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification. HIS 2007: 222-227 | |
| 34 | Thorsten Suttorp, Christian Igel: Resilient Approximation of Kernel Classifiers. ICANN (1) 2007: 139-148 | |
| 33 | Christian Igel, Nikolaus Hansen, Stefan Roth: Covariance Matrix Adaptation for Multi-objective Optimization. Evolutionary Computation 15(1): 1-28 (2007) | |
| 32 | Jens Niehaus, Christian Igel, Wolfgang Banzhaf: Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. Evolutionary Computation 15(2): 199-221 (2007) | |
| 31 | 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) | |
| 30 | 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) | |
| 2006 | ||
| 29 | Christian Igel, Thorsten Suttorp, Nikolaus Hansen: Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. EMO 2006: 171-185 | |
| 28 | Christian Igel, Thorsten Suttorp, Nikolaus Hansen: A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies. GECCO 2006: 453-460 | |
| 27 | Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel: Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. ICANN (2) 2006: 827-836 | |
| 26 | Thorsten Suttorp, Christian Igel: Multi-Objective Optimization of Support Vector Machines. Multi-Objective Machine Learning 2006: 199-220 | |
| 25 | Stefan Roth, Alexander Gepperth, Christian Igel: Multi-Objective Neural Network Optimization for Visual Object Detection. Multi-Objective Machine Learning 2006: 629-655 | |
| 24 | Tobias Glasmachers, Christian Igel: Maximum-Gain Working Set Selection for SVMs. Journal of Machine Learning Research 7: 1437-1466 (2006) | |
| 2005 | ||
| 23 | Susanne Winter, Bernhard Brendel, Christian Igel: Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. Bildverarbeitung für die Medizin 2005: 345-349 | |
| 22 | Christian Igel: Multi-objective Model Selection for Support Vector Machines. EMO 2005: 534-546 | |
| 21 | Christian Igel, Bernhard Sendhoff: Synergies between Evolutionary and Neural Computation. ESANN 2005: 241-252 | |
| 20 | Antonio Pellecchia, Christian Igel, Johann Edelbrunner, Gregor Schöner: Making Driver Modeling Attractive. IEEE Intelligent Systems 20(2): 8-12 (2005) | |
| 19 | Tobias Glasmachers, Christian Igel: Gradient-Based Adaptation of General Gaussian Kernels. Neural Computation 17(10): 2099-2105 (2005) | |
| 18 | Frauke Friedrichs, Christian Igel: Evolutionary tuning of multiple SVM parameters. Neurocomputing 64: 107-117 (2005) | |
| 2004 | ||
| 17 | Stefan Wiegand, Christian Igel, Uwe Handmann: Evolutionary Optimization of Neural Networks for Face Detection. ESANN 2004: 139-144 | |
| 16 | Frauke Friedrichs, Christian Igel: Evolutionary tuning of multiple SVM parameters. ESANN 2004: 519-524 | |
| 15 | Stefan Schneider, Christian Igel, Christian Klaes, Hubert R. Dinse, Jan C. Wiemer: Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience. Genetic Programming and Evolvable Machines 5(2): 215-227 (2004) | |
| 14 | Christian Igel, Karl-Heinz Temme: The chaining syllogism in fuzzy logic. IEEE T. Fuzzy Systems 12(6): 849-853 (2004) | |
| 13 | Stefan Wiegand, Christian Igel, Uwe Handmann: Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection. International Journal of Computational Intelligence and Applications 4(3): 237-254 (2004) | |
| 2003 | ||
| 12 | Christian Igel, Marc Toussaint: Recent Results on No-Free-Lunch Theorems for Optimization CoRR cs.NE/0303032: (2003) | |
| 11 | Christian Igel, Marc Toussaint: On classes of functions for which No Free Lunch results hold. Inf. Process. Lett. 86(6): 317-321 (2003) | |
| 10 | Christian Igel, Marc Toussaint: Neutrality and self-adaptation. Natural Computing 2(2): 117-132 (2003) | |
| 9 | Christian Igel, Michael Hüsken: Empirical evaluation of the improved Rprop learning algorithms. Neurocomputing 50: 105-123 (2003) | |
| 8 | Christian Igel, Martin Kreutz: Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Neurocomputing 55(1-2): 347-361 (2003) | |
| 2002 | ||
| 7 | Michael Hüsken, Christian Igel: Balancing Learning And Evolution. GECCO 2002: 391-398 | |
| 6 | Marc Toussaint, Christian Igel: Neutrality: A Necessity for Self-Adaptation CoRR nlin.AO/0204038: (2002) | |
| 5 | Christian Igel, Peter Stagge: Effects of phenotypic redundancy in structure optimization. IEEE Trans. Evolutionary Computation 6(1): 74-85 (2002) | |
| 4 | Christian Igel, Werner von Seelen, Wolfram Erlhagen, Dirk Jancke: Evolving field models for inhibition effects in early vision. Neurocomputing 44-46: 467-472 (2002) | |
| 2001 | ||
| 3 | Christian Igel, Marc Toussaint: On Classes of Functions for which No Free Lunch Results Hold CoRR cs.NE/0108011: (2001) | |
| 2 | Christian Igel, Wolfram Erlhagen, Dirk Jancke: Optimization of dynamic neural fields. Neurocomputing 36(1-4): 225-233 (2001) | |
| 1997 | ||
| 1 | Christian Igel, Karl-Heinz Temme: Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases. Fuzzy Days 1997: 179-188 | |