| 2009 |
|---|
| 45 | EE | Thomas Voß,
Nikolaus Hansen,
Christian Igel:
Recombination for Learning Strategy Parameters in the MO-CMA-ES.
EMO 2009: 155-168 |
| 2008 |
|---|
| 44 | EE | Verena Heidrich-Meisner,
Christian Igel:
Similarities and differences between policy gradient methods and evolution strategies.
ESANN 2008: 149-154 |
| 43 | EE | Thorsten Suttorp,
Christian Igel:
Approximation of Gaussian process regression models after training.
ESANN 2008: 427-432 |
| 42 | EE | Verena Heidrich-Meisner,
Christian Igel:
Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem.
EWRL 2008: 136-150 |
| 41 | EE | 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 | EE | Tobias Glasmachers,
Christian Igel:
Uncertainty Handling in Model Selection for Support Vector Machines.
PPSN 2008: 185-194 |
| 39 | EE | Verena Heidrich-Meisner,
Christian Igel:
Evolution Strategies for Direct Policy Search.
PPSN 2008: 428-437 |
| 38 | EE | 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 | EE | Tobias Glasmachers,
Christian Igel:
Second-Order SMO Improves SVM Online and Active Learning.
Neural Computation 20(2): 374-382 (2008) |
| 2007 |
|---|
| 36 | EE | Verena Heidrich-Meisner,
Martin Lauer,
Christian Igel,
Martin A. Riedmiller:
Reinforcement learning in a nutshell.
ESANN 2007: 277-288 |
| 35 | EE | Jan Salmen,
Thorsten Suttorp,
Johann Edelbrunner,
Christian Igel:
Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification.
HIS 2007: 222-227 |
| 34 | EE | Thorsten Suttorp,
Christian Igel:
Resilient Approximation of Kernel Classifiers.
ICANN (1) 2007: 139-148 |
| 33 | EE | Christian Igel,
Nikolaus Hansen,
Stefan Roth:
Covariance Matrix Adaptation for Multi-objective Optimization.
Evolutionary Computation 15(1): 1-28 (2007) |
| 32 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Thorsten Suttorp,
Christian Igel:
Multi-Objective Optimization of Support Vector Machines.
Multi-Objective Machine Learning 2006: 199-220 |
| 25 | EE | Stefan Roth,
Alexander Gepperth,
Christian Igel:
Multi-Objective Neural Network Optimization for Visual Object Detection.
Multi-Objective Machine Learning 2006: 629-655 |
| 24 | EE | Tobias Glasmachers,
Christian Igel:
Maximum-Gain Working Set Selection for SVMs.
Journal of Machine Learning Research 7: 1437-1466 (2006) |
| 2005 |
|---|
| 23 | EE | 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 | EE | Christian Igel:
Multi-objective Model Selection for Support Vector Machines.
EMO 2005: 534-546 |
| 21 | EE | Christian Igel,
Bernhard Sendhoff:
Synergies between Evolutionary and Neural Computation.
ESANN 2005: 241-252 |
| 20 | EE | Antonio Pellecchia,
Christian Igel,
Johann Edelbrunner,
Gregor Schöner:
Making Driver Modeling Attractive.
IEEE Intelligent Systems 20(2): 8-12 (2005) |
| 19 | EE | Tobias Glasmachers,
Christian Igel:
Gradient-Based Adaptation of General Gaussian Kernels.
Neural Computation 17(10): 2099-2105 (2005) |
| 18 | EE | Frauke Friedrichs,
Christian Igel:
Evolutionary tuning of multiple SVM parameters.
Neurocomputing 64: 107-117 (2005) |
| 2004 |
|---|
| 17 | EE | Stefan Wiegand,
Christian Igel,
Uwe Handmann:
Evolutionary Optimization of Neural Networks for Face Detection.
ESANN 2004: 139-144 |
| 16 | EE | Frauke Friedrichs,
Christian Igel:
Evolutionary tuning of multiple SVM parameters.
ESANN 2004: 519-524 |
| 15 | EE | 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 | EE | Christian Igel,
Karl-Heinz Temme:
The chaining syllogism in fuzzy logic.
IEEE T. Fuzzy Systems 12(6): 849-853 (2004) |
| 13 | EE | 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 | EE | Christian Igel,
Marc Toussaint:
Recent Results on No-Free-Lunch Theorems for Optimization
CoRR cs.NE/0303032: (2003) |
| 11 | EE | Christian Igel,
Marc Toussaint:
On classes of functions for which No Free Lunch results hold.
Inf. Process. Lett. 86(6): 317-321 (2003) |
| 10 | EE | Christian Igel,
Marc Toussaint:
Neutrality and self-adaptation.
Natural Computing 2(2): 117-132 (2003) |
| 9 | EE | Christian Igel,
Michael Hüsken:
Empirical evaluation of the improved Rprop learning algorithms.
Neurocomputing 50: 105-123 (2003) |
| 8 | EE | 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 | EE | 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 | EE | 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 | EE | Christian Igel,
Marc Toussaint:
On Classes of Functions for which No Free Lunch Results Hold
CoRR cs.NE/0108011: (2001) |
| 2 | EE | 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 |
