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Christian Igel: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Christian Igel
    Multi-objective Model Selection for Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    EMO, 2005, pp:534-546 [Conf]
  2. Christian Igel, Thorsten Suttorp, Nikolaus Hansen
    Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. [Citation Graph (0, 0)][DBLP]
    EMO, 2006, pp:171-185 [Conf]
  3. Frauke Friedrichs, Christian Igel
    Evolutionary tuning of multiple SVM parameters. [Citation Graph (0, 0)][DBLP]
    ESANN, 2004, pp:519-524 [Conf]
  4. Christian Igel, Bernhard Sendhoff
    Synergies between Evolutionary and Neural Computation. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:241-252 [Conf]
  5. Stefan Wiegand, Christian Igel, Uwe Handmann
    Evolutionary Optimization of Neural Networks for Face Detection. [Citation Graph (0, 0)][DBLP]
    ESANN, 2004, pp:139-144 [Conf]
  6. Christian Igel, Karl-Heinz Temme
    Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases. [Citation Graph (0, 0)][DBLP]
    Fuzzy Days, 1997, pp:179-188 [Conf]
  7. Michael Hüsken, Christian Igel
    Balancing Learning And Evolution. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:391-398 [Conf]
  8. Christian Igel, Thorsten Suttorp, Nikolaus Hansen
    A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies. [Citation Graph (0, 0)][DBLP]
    GECCO, 2006, pp:453-460 [Conf]
  9. Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel
    Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2006, pp:827-836 [Conf]
  10. Christian Igel, Marc Toussaint
    On Classes of Functions for which No Free Lunch Results Hold [Citation Graph (0, 0)][DBLP]
    CoRR, 2001, v:0, n:, pp:- [Journal]
  11. Christian Igel, Marc Toussaint
    Recent Results on No-Free-Lunch Theorems for Optimization [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  12. Marc Toussaint, Christian Igel
    Neutrality: A Necessity for Self-Adaptation [Citation Graph (0, 0)][DBLP]
    CoRR, 2002, v:0, n:, pp:- [Journal]
  13. Antonio Pellecchia, Christian Igel, Johann Edelbrunner, Gregor Schöner
    Making Driver Modeling Attractive. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 2005, v:20, n:2, pp:8-12 [Journal]
  14. Stefan Schneider, Christian Igel, Christian Klaes, Hubert R. Dinse, Jan C. Wiemer
    Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience. [Citation Graph (0, 0)][DBLP]
    Genetic Programming and Evolvable Machines, 2004, v:5, n:2, pp:215-227 [Journal]
  15. Stefan Wiegand, Christian Igel, Uwe Handmann
    Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection. [Citation Graph (0, 0)][DBLP]
    International Journal of Computational Intelligence and Applications, 2004, v:4, n:3, pp:237-254 [Journal]
  16. Frauke Friedrichs, Christian Igel
    Evolutionary tuning of multiple SVM parameters. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:64, n:, pp:107-117 [Journal]
  17. Christian Igel, Wolfram Erlhagen, Dirk Jancke
    Optimization of dynamic neural fields. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:36, n:1-4, pp:225-233 [Journal]
  18. Christian Igel, Michael Hüsken
    Empirical evaluation of the improved Rprop learning algorithms. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2003, v:50, n:, pp:105-123 [Journal]
  19. Christian Igel, Martin Kreutz
    Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2003, v:55, n:1-2, pp:347-361 [Journal]
  20. Christian Igel, Werner von Seelen, Wolfram Erlhagen, Dirk Jancke
    Evolving field models for inhibition effects in early vision. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:44, n:, pp:467-472 [Journal]
  21. Christian Igel, Marc Toussaint
    On classes of functions for which No Free Lunch results hold. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 2003, v:86, n:6, pp:317-321 [Journal]
  22. Tobias Glasmachers, Christian Igel
    Maximum-Gain Working Set Selection for SVMs. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1437-1466 [Journal]
  23. Christian Igel, Marc Toussaint
    Neutrality and self-adaptation. [Citation Graph (0, 0)][DBLP]
    Natural Computing, 2003, v:2, n:2, pp:117-132 [Journal]
  24. Tobias Glasmachers, Christian Igel
    Gradient-Based Adaptation of General Gaussian Kernels. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:10, pp:2099-2105 [Journal]
  25. Christian Igel, Peter Stagge
    Effects of phenotypic redundancy in structure optimization. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2002, v:6, n:1, pp:74-85 [Journal]
  26. Christian Igel, Karl-Heinz Temme
    The chaining syllogism in fuzzy logic. [Citation Graph (0, 0)][DBLP]
    IEEE T. Fuzzy Systems, 2004, v:12, n:6, pp:849-853 [Journal]
  27. Thorsten Suttorp, Christian Igel
    Resilient Approximation of Kernel Classifiers. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:139-148 [Conf]
  28. 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. [Citation Graph (0, 0)][DBLP]
    IEEE/ACM Trans. Comput. Biology Bioinform., 2007, v:4, n:2, pp:216-226 [Journal]

  29. Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. [Citation Graph (, )][DBLP]

  30. Recombination for Learning Strategy Parameters in the MO-CMA-ES. [Citation Graph (, )][DBLP]

  31. Reinforcement learning in a nutshell. [Citation Graph (, )][DBLP]

  32. Similarities and differences between policy gradient methods and evolution strategies. [Citation Graph (, )][DBLP]

  33. Approximation of Gaussian process regression models after training. [Citation Graph (, )][DBLP]

  34. Uncertainty handling CMA-ES for reinforcement learning. [Citation Graph (, )][DBLP]

  35. Improved step size adaptation for the MO-CMA-ES. [Citation Graph (, )][DBLP]

  36. Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study. [Citation Graph (, )][DBLP]

  37. Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification. [Citation Graph (, )][DBLP]

  38. Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. [Citation Graph (, )][DBLP]

  39. Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search. [Citation Graph (, )][DBLP]

  40. Evolution Strategies for Direct Policy Search. [Citation Graph (, )][DBLP]

  41. Uncertainty Handling in Model Selection for Support Vector Machines. [Citation Graph (, )][DBLP]

  42. New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. [Citation Graph (, )][DBLP]

  43. Scalarization versus indicator-based selection in multi-objective CMA evolution strategies. [Citation Graph (, )][DBLP]

  44. Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. [Citation Graph (, )][DBLP]

  45. Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. [Citation Graph (, )][DBLP]

  46. Covariance Matrix Adaptation for Multi-objective Optimization. [Citation Graph (, )][DBLP]

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