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Publikationen

Zeige Ergebnisse 1 bis 10 von 506.
  1. Kristian Kersting; Luc De Raedt; Bernd Gutmann; Andreas Karwath; Niels Landwehr

    Relational Sequence Learning

    In: Luc De Raedt; Paolo Frasconi; Kristian Kersting; Stephen H. Muggleton (Hrsg.). Probabilistic Inductive Logic Programming - Theory and Applications. Pages 28-55, Lecture Notes in Computer Science, Vol. 4911, Springer, 2008.

  2. Bernd Gutmann; Angelika Kimmig; Kristian Kersting; Luc De Raedt

    Parameter Learning in Probabilistic Databases: A Least Squares Approach

    In: Walter Daelemans; Bart Goethals; Katharina Morik (Hrsg.). Machine Learning and Knowledge Discovery in Databases, European Conference, Proceedings. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2008), September 15-19, Antwerp, Belgium, Pages 473-488, Lecture Notes in Computer Science, Vol. 5211, Springer, 2008.

  3. Christian Plagemann; Kristian Kersting; Wolfram Burgard

    Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness

    In: Walter Daelemans; Bart Goethals; Katharina Morik (Hrsg.). Machine Learning and Knowledge Discovery in Databases, European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2008), September 15-19, Antwerp, Belgium, Pages 204-219, Lecture Notes in Computer Science, Vol. 5212, Springer, 2008.

  4. Gustavo Alonso; Donald Kossmann; Timothy Roscoe; Nesime Tatbul; Andrew Baumann; Carsten Binnig; Peter M. Fischer; Oriana Riva; Jens Teubner

    The ETH Zurich systems group and enterprise computing center

    In: SIGMOD Record, Vol. 37, No. 4, Pages 94-99, Association for Computing Machinery (ACM), 2008.

  5. Carsten Binnig; Donald Kossmann; Eric Lo

    Towards Automatic Test Database Generation

    In: IEEE Data Engineering Bulletin, Vol. 31, No. 1, Pages 28-35, IEEE, 2008.

  6. Generating meaningful test databases

    PhD-Thesis, University of Heidelberg, Germany, 2008.

  7. Hirotaka Hachiya; Takayuki Akiyama; Masashi Sugiyama; Jan Peters

    Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation

    In: Dieter Fox; Carla P. Gomes (Hrsg.). Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence (AAAI-2008), July 13-17, Chicago, Illinois, USA, Pages 1351-1356, AAAI Press, 2008.

  8. Jan Peters; Stefan Schaal

    Reinforcement learning of motor skills with policy gradients

    In: Neural Networks, Vol. 21, No. 4, Pages 682-697, Elsevier, 2008.

  9. Jan Peters; Stefan Schaal

    Natural Actor-Critic

    In: Neurocomputing, Vol. 71, No. 7-9, Pages 1180-1190, Elsevier, 2008.

  10. Duy Nguyen-Tuong; Matthias W. Seeger; Jan Peters

    Local Gaussian Process Regression for Real Time Online Model Learning

    In: Daphne Koller; Dale Schuurmans; Yoshua Bengio; Léon Bottou (Hrsg.). Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems. Neural Information Processing Systems (NeurIPS-2008), December 8-11, Vancouver, British Columbia, Canada, Pages 1193-1200, Curran Associates, Inc. 2008.