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Publications

Displaying results 341 to 350 of 571.

  1. Riad Akrour; Asma Atamna; Jan Peters

    Convex optimization with an interpolation-based projection and its application to deep learning

    In: Machine Learning, Vol. 110, No. 8, Pages 2267-2289, Springer, 2021.

  2. Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters; Marcello Restelli

    Gaussian Approximation for Bias Reduction in Q-Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 277:1-277:51, JMLR, 2021.

  3. Niyati Rawal; Dorothea Koert; Cigdem Turan; Kristian Kersting; Jan Peters; Ruth Stock-Homburg

    ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition

    In: Frontiers in Robotics and AI, Vol. 8, Pages 0-10, Frontiers, 2021.

  4. Bang You; Jingming Xie; Youping Chen; Jan Peters; Oleg Arenz

    Self-supervised Sequential Information Bottleneck for Robust Exploration in Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2209.05333, Pages 0-10, arXiv, 2022.

  5. Riad Akrour; Filipe Veiga; Jan Peters; Gerhard Neumann

    Regularizing Reinforcement Learning with State Abstraction

    In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2018), October 1-5, Madrid, Spain, Pages 534-539, IEEE, 2018.

  6. Paavo Parmas; Carl Edward Rasmussen; Jan Peters; Kenji Doya

    PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

    In: Jennifer G. Dy; Andreas Krause (Hrsg.). Proceedings of the 35th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2018), July 10-15, Stockholm, Sweden, Pages 4062-4071, Proceedings of Machine Learning Research, Vol. 80, PMLR, 2018.

  7. Michael Lutter; Kim Listmann; Jan Peters

    Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

    In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), November 3-8, Macau, China, Pages 7718-7725, IEEE, 2019.

  8. Michael Lutter; Christian Ritter; Jan Peters

    Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

    In: 7th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2019), May 6-9, New Orleans, LA, USA, OpenReview.net, 2019.

  9. Daniel Tanneberg; Alexandros Paraschos; Jan Peters; Elmar Rueckert

    Deep spiking networks for model-based planning in humanoids

    In: 16th IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2016), November 15-17, Cancun, Mexico, Pages 656-661, IEEE, 2016.

  10. Riad Akrour; Davide Tateo; Jan Peters

    Reinforcement Learning from a Mixture of Interpretable Experts

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2006.05911, Pages 0-10, arXiv, 2020.

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