Christian Igel

Christian Igel

Professor

Member of:

    Introductory remarks on publicationslist

    This list of pubications is not fully complete.

    For a complete list of older publications as well as papers and software available online please vist my old homepage: https://christian-igel.github.io

    I also maintain a Google Scholar profile: https://scholar.google.dk/citations?user=d-jF4zIAAAAJ


    1. 2007
    2. Resilient approximation of kernel classifiers

      Suttorp, T. & Igel, Christian, 2007, Artificial Neural Networks – ICANN 2007: 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part I. de Sá, J. M., Alexandre, L. A., Duch, W. & Mandic, D. (eds.). Springer, Vol. Part I. p. 139-148 10 p. (Lecture notes in computer science, Vol. 4668).

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    3. Steady-state selection and efficient covariance matrix update in the multi-objective CMA-ES

      Igel, Christian, Suttorp, T. & Hansen, N., 2007, Evolutionary Multi-Criterion Optimization: 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007. Proceedings. Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T. & Murata, T. (eds.). Springer, p. 171-185 15 p. (Lecture notes in computer science, Vol. 4403).

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    4. 2006
    5. A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies

      Igel, Christian, Suttorp, T. & Hansen, N., 2006, Proceedings of the 8th annual Conference on Genetic and Evolutionary Computation: GECCO '06. Association for Computing Machinery, p. 453-460 8 p.

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    6. Computational efficient covariance matrix update and the multi-objective variable metric evolution strategy

      Igel, Christian, 2006, Theory of Evolutionary Algorithms. Arnold, D. V., Jansen, T., Rowe, J. E. & Vose, M. D. (eds.). Schloss Dagstuhl - Leibniz-Zentrum für Informatik, p. 7 1 p. (Dagstuhl Seminar Proceedings, Vol. 06061).

      Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsResearch

    7. Evolutionary optimization of sequence kernels for detection of bacterial gene starts

      Mersch, B., Glasmachers, T., Meinicke, P. & Igel, Christian, 2006, Artificial Neural Networks – ICANN 2006: 16th International Conference, Athens, Greece, September 10-14, 2006. Proceedings, Part II. Kollias, S., Stafylopatis, A., Duch, W. & Oja, E. (eds.). Springer, p. 827-836 10 p. (Lecture notes in computer science, Vol. 4132).

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    8. Maximum-gain working set selection for support vector machines

      Glasmachers, T. & Igel, Christian, 2006, In: Journal of Machine Learning Research. 7, p. 1437-1466 30 p.

      Research output: Contribution to journalJournal articleResearchpeer-review

    9. Modelling dynamic activity patterns in early visual cortex based on voltage sensitive dye experiments

      Meyer, J., Igel, Christian & Jancke, D., 2006, Neuro-Visionen 3. Perspektiven in Nordrhein-Westfalen: Symposium der Nordrhein-westfälischen Akademie der Wissenschaften 2005. Hossmann, K-A. (ed.). Verlag Ferdinand Schöningh, p. 193-195 3 p.

      Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsResearch

    10. Multi-objective neural network optimization for visual object detection

      Roth, S., Gepperth, A. & Igel, Christian, 2006, Multi-objective machine learning. Jin, Y. (ed.). Vol. V. p. 629-655 27 p. (Studies in Computational Intelligence, Vol. 16).

      Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

    11. Multi-objective optimization of support vector machines

      Suttorp, T. & Igel, Christian, 2006, Multi-objective machine learning. Jin, Y. (ed.). Springer, p. 199-220 22 p. (Studies in Computational Intelligence, Vol. 16).

      Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

    12. 2005
    13. Evolutionary optimization of neural systems: the use of strategy adaptation

      Igel, Christian, Wiegand, S. & Friedrichs, F., 2005, Trends and applications in constructive approximation. Mache, D. H., Szabados, J. & de Bruin, M. G. (eds.). Birkhäuser Verlag, p. 103-123 21 p. (International Series of Numerical Mathematics, Vol. 151).

      Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

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