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Publikationen

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  1. Shuo Yang; Tushar Khot; Kristian Kersting; Sriraam Natarajan

    Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach

    In: Dale Schuurmans; Michael P. Wellman (Hrsg.). Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI Conference on …

  2. Marion Neumann; Roman Garnett; Christian Bauckhage; Kristian Kersting

    Propagation kernels: efficient graph kernels from propagated information

    In: Machine Learning, Vol. 102, No. 2, Pages 209-245, Springer, 2016.

  3. Piotr Szymanski; Tomasz Kajdanowicz; Kristian Kersting

    How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?

    In: Entropy, Vol. 18, No. 8, Pages 0-10, MDPI, 2016.

  4. Jan Peters; Daniel D. Lee; Jens Kober; Duy Nguyen-Tuong; J. Andrew Bagnell; Stefan Schaal

    Robot Learning

    In: Bruno Siciliano; Oussama Khatib (Hrsg.). Springer Handbook of Robotics. Pages 357-398, Springer Handbooks, Springer, 2016.

  5. Christian Daniel; Gerhard Neumann; Oliver Kroemer; Jan Peters

    Hierarchical Relative Entropy Policy Search

    In: Journal of Machine Learning Research, Vol. 17, Pages 93:1-93:50, JMLR, 2016.

  6. Christian Daniel; Herke van Hoof; Jan Peters; Gerhard Neumann

    Probabilistic inference for determining options in reinforcement learning

    In: Machine Learning, Vol. 104, No. 2-3, Pages 337-357, Springer, 2016.