Fabian Cristian Gieseke

Fabian Cristian Gieseke

Associate Professor


  1. 2014
  2. Published

    A framework for data mining in wind power time series

    Kramer, O., Gieseke, Fabian Cristian, Heinermann, J., Poloczek, J. & Treiber, N. A., 2014, Data analytics for renewable energy integration: Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers. Woon, W. L., Aung, Z. & Madnick, S. (eds.). Springer, p. 97-107 (Lecture notes in computer science, Vol. 8817).

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

  3. Published

    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 p. (JMLR: Workshop and Conference Proceedings, Vol. 32).

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

  4. Fast and simple gradient-based optimization for semi-supervised support vector machines

    Gieseke, Fabian Cristian, Airola, A., Pahikkala, T. & Kramer, O., 2014, In: Neurocomputing. 123, p. 23-32 10 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. Published

    Improving the performance of photometric regression models via massive parallel feature selection

    Polsterer, K. L., Gieseke, Fabian Cristian, Igel, Christian & Goto, T., 2014, Astronomical Data Analysis Software and Systems XXIII. Manset, N. & Forshay, P. (eds.). Astronomical Society of the Pacific, Vol. 485. p. 425-428 4 p. (Astronomical Society of the Pacific. Conference Proceedings, Vol. 485).

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

  6. Published

    On unsupervised training of multi-class regularized least-squares classifiers

    Pahikkala, T., Airola, A., Gieseke, Fabian Cristian & Kramer, O., 2014, In: Journal of Computer Science and Technology. 29, 1, p. 90-104 15 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  7. Published

    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. (ed.). i6doc.com, p. 87-92 6 p.

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

ID: 91244670