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Publications

Displaying results 481 to 490 of 14533.

  1. Silvia Chiappa; Jens Kober; Jan Peters

    Using Bayesian Dynamical Systems for Motion Template Libraries

    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 297-304, Curran Associates, Inc. 2008.

  2. 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.

  3. Jan Peters; Stefan Schaal

    Reinforcement learning of motor skills with policy gradients

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

  4. Jan Peters; Stefan Schaal

    Natural Actor-Critic

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

  5. Matthew Hoffman; Nando de Freitas; Arnaud Doucet; Jan Peters

    An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward

    In: David A. Van Dyk; Max Welling (Hrsg.). Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics (AISTATS-2009), April 16-18, Clearwater Beach, Florida, USA, Pages 232-239, JMLR Proceedings, Vol. 5, JMLR.org, 2009.

  6. Jan Peters; Jun Morimoto; Russ Tedrake; Nicholas Roy

    Robot learning [TC Spotlight]

    In: IEEE Robotics & Automation Magazine, Vol. 16, No. 3, Pages 19-20, IEEE, 2009.

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

    Adaptive importance sampling for value function approximation in off-policy reinforcement learning

    In: Neural Networks, Vol. 22, No. 10, Pages 1399-1410, Elsevier, 2009.

  8. Marc Peter Deisenroth; Carl Edward Rasmussen; Jan Peters

    Gaussian process dynamic programming

    In: Neurocomputing, Vol. 72, No. 7-9, Pages 1508-1524, Elsevier, 2009.

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

    Model Learning with Local Gaussian Process Regression

    In: Advanced Robotics, Vol. 23, No. 15, Pages 2015-2034, Taylor & Francis Online, 2009.

  10. Oliver Kroemer; Renaud Detry; Justus H. Piater; Jan Peters

    Combining active learning and reactive control for robot grasping

    In: Robotics and Autonomous Systems (RAS), Vol. 58, No. 9, Pages 1105-1116, Elsevier, 2010.

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