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Year: 2008
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Displaying results 1 to 10 of 506.

  1. Kristian Kersting; Luc De Raedt

    Basic Principles of Learning Bayesian Logic Programs

    In: Luc De Raedt; Paolo Frasconi; Kristian Kersting; Stephen H. Muggleton (Hrsg.). Probabilistic Inductive Logic Programming - Theory and Applications. Pages 189-221, Lecture Notes in Computer Science, Vol. 4911, Springer, 2008.

  2. Carsten Binnig; Donald Kossmann; Eric Lo

    Multi-RQP: generating test databases for the functional testing of OLTP applications

    In: Leo Giakoumakis; Donald Kossmann (Hrsg.). Proceedings of the 1st International Workshop on Testing Database Systems. International Workshop on Testing Database Systems (DBTest-2008), June 13, Vancouver, BC, Canada, ACM, 2008.

  3. Carsten Binnig; Donald Kossmann; Eric Lo; Angel Saenz-Badillos

    Automatic Result Verification for the Functional Testing of a Query Language

    In: Gustavo Alonso; José A. Blakeley; Arbee L. P. Chen (Hrsg.). Proceedings of the 24th International Conference on Data Engineering. IEEE International Conference on Data Engineering (ICDE-2008), April 7-12, Cancún, Mexico, Pages 1534-1536, IEEE Computer Society, 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. Carsten Binnig

    Generating meaningful test databases

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

  7. 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.

  8. 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.

  9. 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.

  10. Zhao Xu; Volker Tresp; Achim Rettinger; Kristian Kersting

    Social Network Mining with Nonparametric Relational Models

    In: C. Lee Giles; Marc Smith; John Yen; Haizheng Zhang (Hrsg.). Advances in Social Network Mining and Analysis, Second International Workshop, SNAKDD 2008, Revised Selected Papers. International Workshop on Social Network Mining and Analysis (SNAKDD-2008), August 24-27, Las Vegas, NV, USA, Pages 77-96, Lecture Notes in Computer Science (LNCS), Vol. 5498, Springer, 2008.

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