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Publikationen

Zeige Ergebnisse 21 bis 30 von 507.
  1. Riad Akrour; Dmitry Sorokin; Jan Peters; Gerhard Neumann

    Local Bayesian Optimization of Motor Skills

    In: Doina Precup; Yee Whye Teh (Hrsg.). Proceedings of the 34th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2017), August 6-11, Sydney, NSW, Australia, Pages 41-50, Proceedings of Machine Learning Research, Vol. 70, PMLR, 2017.

  2. Elmar Rueckert; Moritz Nakatenus; Samuele Tosatto; Jan Peters

    Learning inverse dynamics models in O(n) time with LSTM networks

    In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE-RAS International Conference on Humanoid Robots (Humanoids-2017), November 15-17, Birmingham, United Kingdom, Pages 811-816, IEEE, 2017.

  3. Svenja Stark; Jan Peters; Elmar Rueckert

    A comparison of distance measures for learning nonparametric motor skill libraries

    In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE-RAS International Conference on Humanoid Robots (Humanoids-2017), November 15-17, Birmingham, United Kingdom, Pages 624-630, IEEE, 2017.

  4. Daniel Tanneberg; Jan Peters; Elmar Rueckert

    Efficient online adaptation with stochastic recurrent neural networks

    In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE-RAS International Conference on Humanoid Robots (Humanoids-2017), November 15-17, Birmingham, United Kingdom, Pages 198-204, IEEE, 2017.

  5. Lukas Großberger; Matthias R. Hohmann; Jan Peters; Moritz Grosse-Wentrup

    Investigating Music imagery as a Cognitive Paradigm for low-Cost brain-Computer Interfaces

    In: Gernot R. Müller-Putz; David Steyrl; Selina C. Wriessnegger; Reinhold Scherer (Hrsg.). From Vision to Reality - Proceedings of the 7th Graz Brain-Computer Interface Conference 2017. Graz Brain-Computer Interface Conference (GBCIC-2017), September 18-22, Graz, Austria, ISBN 978-3-85125-533-1, Verlag der Technischen Universitaet Graz, 2017.

  6. Daniel Tanneberg; Jan Peters; Elmar Rueckert

    Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals

    In: Proceedings of the 1st Annual Conference on Robot Learning. Conference on Robot Learning (CoRL-2017), November 13-15, Mountain View, California, USA, Pages 167-174, Proceedings of Machine Learning Research, Vol. 78, PMLR, 2017.

  7. Fraser Bowen; Jon Dehdari; Josef van Genabith

    The Effect of Error Rate in Artificially Generated Data for Automatic Preposition and Determiner Correction

    In: The Third Workshop on Noisy User-generated Text (W-NUT 2017) - Proceedings of the Workshop. Workshop on Noisy User-generated Text (NUT-2017), located at EMNLP 2017, September 7, Copenhagen, Denmark, Pages 68-76, ISBN 978-1-945626-94-4, Association for Computational Linguistics, 9/2017.

  8. Nijat Mehdiyev; Johannes Lahann; Andreas Emrich; David Enke; Peter Fettke; Peter Loos

    Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry

    In: Procedia Computer Science. Complex Adaptive Systems (CAS-2017), USA, Pages 242-249, Vol. 114, 2017.

  9. DeepBIBX: Deep Learning for Image Based Bibliographic Data Extraction

    In: International Conference on Neural Information Processing. International Conference on Neural Information Processing (ICONIP-2017), 24th International Conference on Neural Information Processing, November 14-18, Guangzhou, China, Pages 286-293, Vol. 10635, ISBN 978-3-319-70095-3, Springer, 10/2017.

  10. Hans-Wolfgang Micklitz; Lucia Reisch; Gesche Joost; Helga Zander-Hayat (Hrsg.)

    Verbraucherrecht 2.0 - Verbraucher in der digitalen Welt

    ISBN 9783848741878, Nomos, 2017.