Fabian Cristian Gieseke

Fabian Cristian Gieseke

Associate Professor


Publication year:
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31 - 40 out of 73Page size: 10
  1. 2014
  2. 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 proceeding › Article in proceedings › Research › peer-review

  3. 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 journal › Journal article › Research › peer-review

  4. 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 proceeding › Article in proceedings › Research › peer-review

  5. 2015

  6. An efficient many-core implementation for semi-supervised support vector machines

    Gieseke, Fabian Cristian, 2015, Machine Learning, Optimization, and Big Data: First International Workshop, MOD 2015, Taormina, Sicily, Italy, July 21-23, 2015, Revised Selected Papers. Pardalos, P., Pavone, M., Farinella, G. M. & Cutello, V. (eds.). Springer, p. 145-157 13 p. (Lecture notes in computer science, Vol. 9432).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  7. Analyzing complex and structured data via unsupervised learning techniques

    Polsterer, K. L., Gieseke, Fabian Cristian, Gianniotis, N. & Kügler, D., 2015.

    Research output: Contribution to conference › Paper › Research

  8. Published

    Automatic galaxy classification via machine learning techniques: Parallelized rotation/flipping INvariant Kohonen maps (PINK)

    Polsterer, K. L., Gieseke, Fabian Cristian & Igel, Christian, 2015, Astronomical Data Analysis Software and Systems: Proceedings of a meeting held at Calgary, Alberta, Canada 5-9 October 2014. Taylor, A. R. & Rosolowsky, E. (eds.). Astronomical Society of the Pacific, Vol. 24. p. 81-86 6 p. (ASP Conference Series, Vol. 495).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  9. Batch steepest-descent-mildest-ascent for interactive maximum margin clustering

    Gieseke, Fabian Cristian, Pahikkala, T. & Heskes, T., 2015, Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. Fromont, E., De Bie, T. & van Leeuwen, M. (eds.). Springer, p. 95-107 13 p. (Lecture notes in computer science, Vol. 9385).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  10. DRACULA: Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy

    Aguena, M., Busti, V. C., Camacho, H., Sasdelli, M., Ishida, E. E. O., Vilalta, R., Trindade, A. M. M., Gieseke, Fabian Cristian, de Souza, R. S. & Fantaye, Y. T., 2015

    Research output: Non-textual form › Computer programme › Research

  11. Published

    Nearest neighbor density ratio estimation for large-scale applications in astronomy

    Kremer, J., Gieseke, Fabian Cristian, Steenstrup Pedersen, Kim & Igel, Christian, 2015, In: Astronomy and Computing. 12, p. 67-72 6 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  12. 2016

  13. Exploring the spectroscopic diversity of Type Ia supernovae with DRACULA: a machine learning approach

    Sasdelli, M., Ishida, E. E. O., Vilalta, R., Aguena, M., Busti, V. C., Camacho, H., Trindade, A. M. M., Gieseke, Fabian Cristian, de Souza, R. S., Fantaye, Y. T. & Mazzali, P. A., 2016, In: Monthly Notices of the Royal Astronomical Society. 461, 2, p. 2044-2059 16 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

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