Christian Igel

Christian Igel

Professor

Medlem af:

    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


    1. Uncertainty handling in evolutionary direct policy search

      Heidrich-Meisner, V. & Igel, Christian, 2008. 8 s.

      Publikation: KonferencebidragPaperForskningfagfællebedømt

    2. Uncertainty handling CMA-ES for reinforcement learning

      Heidrich-Meisner, V. & Igel, Christian, 2009, Proceedings of the 11th Annual conference on Genetic and evolutionary computation: GECCO '09. Association for Computing Machinery, s. 1211-1218 8 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    3. Reinforcement learning in a nutshell

      Heidrich-Meisner, V., Lauer, M., Igel, Christian & Riedmiller, M., 2007, ESANN 2007: 15th European Symposium on Artificial Neural Networks. D-side Publications, s. 277-288 12 s. ES2007-4

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    4. Evolution strategies for direct policy search

      Heidrich-Meisner, V. & Igel, Christian, 2008, Parallel Problem Solving from Nature – PPSN X: 10th International Conference, Dortmund, Germany, September 13-17, 2008. Proceedings. Rudolph, G., Jansen, T., Beume, N., Lucas, S. & Poloni, C. (red.). Springer, s. 428-437 10 s. (Lecture notes in computer science, Bind 5199).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    5. Variable-metric evolution strategies for direct policy search

      Heidrich-Meisner, V. & Igel, Christian, 2009. 2 s.

      Publikation: KonferencebidragKonferenceabstrakt til konferenceForskningfagfællebedømt

    6. Udgivet

      Non-linearly increasing resampling in racing algorithms

      Heidrich-Meisner, V. & Igel, Christian, 2011, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2011). Verleysen, M. (red.). s. 465-470 6 s.

      Publikation: Bidrag til bog/antologi/rapportKonferenceabstrakt i proceedingsForskningfagfællebedømt

    7. Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search

      Heidrich-Meisner, V. & Igel, Christian, 2009, Proceedings of the 26th International Conference on Machine Learning (ICML 2009). Association for Computing Machinery, s. 401-408 8 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    8. Direct policy search: intrinsic vs. extrinsic perturbations

      Heidrich-Meisner, V. & Igel, Christian, 2010, Workshop New Challenges in Neural Computation . Hammer, B. & Villmann, T. (red.). s. 33-39 7 s. (Machine Learning Reports, Bind 04/2010).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    9. Uncertainty handling in model selection for support vector machines

      Glasmachers, T. & Igel, Christian, 2008, Parallel Problem Solving from Nature – PPSN X: 10th International Conference, Dortmund, Germany, September 13-17, 2008. Proceedings. Rudolph, G., Jansen, T., Beume, N., Lucas, S. & Poloni, C. (red.). Springer, s. 185-194 10 s. (Lecture notes in computer science, Bind 5199).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    10. Second-order SMO improves SVM online and active learning

      Glasmachers, T. & Igel, Christian, 2008, I: Neural Computation. 20, 2, s. 374-382 9 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    11. Gradient-based adaptation of general gaussian kernels

      Glasmachers, T. & Igel, Christian, 2005, I: Neural Computation. 17, 10, s. 2099-2105 7 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    12. Maximum likelihood model selection for 1-norm soft margin SVMs with multiple parameters

      Glasmachers, T. & Igel, Christian, 2010, I: IEEE Transactions on Pattern Analysis and Machine Intelligence. 32, 8, s. 1522-1528 7 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

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

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

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    14. Udgivet

      Polynomial runtime bounds for fixed-rank unsupervised least-squares classification

      Gieseke, Fabian Cristian, Pahikkala, T. & Igel, Christian, 2013, Asian Conference on Machine Learning. Ong, C. S. & Ho, T. B. (red.). Bind 29. s. 62-71 10 s. (JMLR: Workshop and Conference Proceedings, Bind 29).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    15. Udgivet

      bufferkdtree: a Python library for massive nearest neighbor queries on multi-many-core devices

      Gieseke, Fabian Cristian, Oancea, Cosmin Eugen & Igel, Christian, 15 mar. 2017, I: Knowledge-Based Systems. 120, s. 1-3 3 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskning

    16. Udgivet

      Buffer k-d trees: processing massive nearest neighbor queries on GPUs

      Gieseke, Fabian Cristian, Heinermann, J., Oancea, Cosmin Eugen & Igel, Christian, 2014, Proceedings of the 31st International Conference on Machine Learning, Beijing, China, 2014. 9 s. (JMLR: Workshop and Conference Proceedings, Bind 32).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    17. Udgivet

      Speedy greedy feature selection: better redshift estimation via massive parallelism

      Gieseke, Fabian Cristian, Polsterer, K. L., Oancea, Cosmin Eugen & Igel, Christian, 2014, ESANN 2014 proceedings: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen, M. (red.). i6doc.com, s. 87-92 6 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    18. Udgivet

      Bigger buffer k-d trees on multi-many-core systems

      Gieseke, Fabian Cristian, Oancea, Cosmin Eugen, Mahabal, A., Igel, Christian & Heskes, T., 2019, High Performance Computing for Computational Science – VECPAR 2018: 13th International Conference, São Pedro, Brazil, September 17–19, 2018, Revised Selected Papers. Springer, s. 202-214 (Lecture Notes in Computer Science, Bind 11333).

      Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

    19. Udgivet

      Training big random forests with little resources

      Gieseke, Fabian Cristian & Igel, Christian, 2018, KDD 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Association for Computing Machinery, s. 1445-1454

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    20. Udgivet

      Massively-parallel best subset selection for ordinary least-squares regression

      Gieseke, F., Polsterer, K. L., Mahabal, A., Igel, Christian & Heskes, T., 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings. IEEE, s. 1-8 8 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    21. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    22. Evolutionary tuning of multiple SVM parameters

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

      Publikation: Bidrag til tidsskriftKonferenceartikelForskningfagfællebedømt

    23. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    24. Udgivet

      Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow

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

      Publikation: KonferencebidragPaperForskningfagfællebedømt

    25. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

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