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Publications

Page 29 of 30.

  1. 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.

  2. 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.

  3. 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.

  4. Kristian Kersting; Christian Plagemann; Alexandru Cocora; Wolfram Burgard; Luc De Raedt

    Learning to transfer optimal navigation policies

    In: Advanced Robotics, Vol. 21, No. 13, Pages 1565-1582, Taylor & Francis Online, 2007.

  5. Kristian Kersting; Christian Plagemann; Patrick Pfaff; Wolfram Burgard

    Most likely heteroscedastic Gaussian process regression

    In: Zoubin Ghahramani (Hrsg.). Machine Learning, Proceedings of the Twenty-Fourth International Conference. International Conference on Machine Learning (ICML-2007), Pages 393-400, ACM International Conference Proceeding Series, Vol. 227, ACM, 2007.

  6. Luc De Raedt; Thomas G. Dietterich; Lise Getoor; Kristian Kersting; Stephen H. Muggleton (Hrsg.)

    07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis

    Probabilistic, Logical and Relational Learning - A Further Synthesis, April 14-20, Schloss Dagstuhl, Germany, Dagstuhl Seminar Proceedings, Vol. 07161, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, 2007.

  7. Kristian Kersting

    An inductive logic programming approach to statistical relational learning

    In: AI Communications (AIC), Vol. 19, No. 4, Pages 389-390, IOS Press, 2006.

  8. Uwe Dick; Kristian Kersting

    Fisher Kernels for Relational Data

    In: Johannes Fürnkranz; Tobias Scheffer; Myra Spiliopoulou (Hrsg.). Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Proceedings. European Conference on Machine Learning (ECML-2006), September 18-22, Berlin, Germany, Pages 114-125, Lecture Notes in Computer Science (LNCS), Vol. 4212, Springer, 2006.

  9. Bernd Gutmann; Kristian Kersting

    TildeCRF: Conditional Random Fields for Logical Sequences

    In: Johannes Fürnkranz; Tobias Scheffer; Myra Spiliopoulou (Hrsg.). Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Proceedings. European Conference on Machine Learning (ECML-2006), September 18-22, Berlin, Germany, Pages 174-185, Lecture Notes in Computer Science (LNCS), Vol. 4212, Springer, 2006.

  10. Rudolph Triebel; Kristian Kersting; Wolfram Burgard

    Robust 3D Scan Point Classification using Associative Markov Networks

    In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation (ICRA-2006), May 15-19, Orlando, Florida, USA, Pages 2603-2608, IEEE, 2006.