Christian Igel

Christian Igel

Professor

Medlem af:

    ORCID: 0000-0003-2868-0856

    Kommentarer til publikationsliste

    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: http://image.diku.dk/igel

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


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    1. Evolutionary tuning of multiple SVM parameters

      Friedrichs, F. & Igel, Christian, 2004, ESANN 2004: 12th European Symposium on Artificial Neural Networks. D-side Publications, s. 519-524 6 s.

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    2. Evolutionary tuning of multiple SVM parameters

      Friedrichs, F. & Igel, Christian, 2005, I: Neurocomputing. 64, s. 107-117 11 s.

      Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

    3. Udgivet

      The logarithmic hypervolume indicator

      Friedrich, T., Bringmann, K., Voß, T. & Igel, Christian, 2011, Proceedings of the 11th Workshop on Foundations of genetic algorithms : FOGA '11. Beyer, H-G. & Langdon, W. B. (red.). Association for Computing Machinery, s. 81-91 11 s.

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    4. Udgivet

      Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow

      Florescu, C. & Igel, Christian, 2018. 5 s.

      Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt

    5. Challenges in training restricted Boltzmann machines

      Fischer, A. & Igel, Christian, 2010, Workshop New Challenges in Neural Computation 2010. Hammer, B. & Villmann, T. (red.). s. 11-24 14 s. (Machine Learning Reports; Nr. 04/2010).

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    6. Empirical analysis of the divergence of Gibbs sampling based learning algorithms for restricted Boltzmann machines

      Fischer, A. & Igel, Christian, 2010, Artificial Neural Networks – ICANN 201: 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part III. Diamantaras, K., Duch, W. & Iliadis, L. S. (red.). Springer, s. 208-217 10 s. (Lecture notes in computer science, Bind 6354).

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    7. Udgivet

      Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives

      Fischer, A. & Igel, Christian, 2011, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2011). Verleysen, M. (red.). ESANN , s. 495-500 6 s.

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    8. Contrastive divergence learning may diverge when training restricted Boltzmann machines

      Fischer, A. & Igel, Christian, 2009, I: Frontiers in Computational Neuroscience.

      Publikation: Bidrag til tidsskrift › Konferenceabstrakt i tidsskrift › Forskning › fagfællebedømt

    9. Udgivet

      An introduction to restricted Boltzmann machines

      Fischer, A. & Igel, Christian, 2012, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, Argentina, September 3-6, 2012. Proceedings. Alvarez, L., Mejail, M., Gomez, L. & Jacobo, J. (red.). Springer, s. 14-36 23 s. (Lecture notes in computer science, Bind 7441).

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    10. Udgivet

      A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines

      Fischer, A. & Igel, Christian, 2015, I: Theoretical Computer Science. 598, s. 102-117 16 s.

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

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