Fabian Cristian Gieseke

Fabian Cristian Gieseke

Associate Professor


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  1. 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

  2. Speedy local search for semi-supervised regularized least-squares

    Gieseke, Fabian Cristian, Kramer, O., Airola, A. & Pahikkala, T., 2011, KI 2011: Advances in Artificial Intelligence : - 34th Annual German Conference on AI, Proceedings. Bach, J. & Edelkamp, S. (eds.). p. 87-98 12 p. (Lecture notes in computer science, Vol. 7006).

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

  3. Published

    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, p. 1445-1454

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

  4. From supervised to unsupervised support vector machines and applications in astronomy

    Gieseke, Fabian Cristian, 2013, In: KI - Künstliche Intelligenz. 27, 3, p. 281-285 5 p.

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

  5. Towards non-linear constraint estimation for expensive optimization

    Gieseke, Fabian Cristian & Kramer, O., 2013, Applications of Evolutionary Computation: 16th European Conference, EvoApplications 2013, Vienna, Austria, April 3-5, 2013. Proceedings. Esparcia-Alcázar, A. I. (ed.). Springer, p. 459-468 10 p. (Lecture notes in computer science, Vol. 7835).

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

  6. Published

    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. (eds.). Vol. 29. p. 62-71 10 p. (JMLR: Workshop and Conference Proceedings, Vol. 29).

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

  7. Published

    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, In: Knowledge-Based Systems. 120, p. 1-3 3 p.

    Research output: Contribution to journal › Journal article › Research

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

  9. 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

  10. Published

    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, p. 202-214 (Lecture Notes in Computer Science, Vol. 11333).

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

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