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Publications

Displaying results 291 to 300 of 682.

  1. Michael Lutter; Shie Mannor; Jan Peters; Dieter Fox; Animesh Garg

    Value Iteration in Continuous Actions, States and Time

    In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2021), July 18-24, Pages 7224-7234, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Tuan Dam; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2202.07071, Pages 0-10, arXiv, 2022.

  7. Vignesh Prasad; Dorothea Koert; Ruth Stock-Homburg; Jan Peters; Georgia Chalvatzaki

    MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction

    In: 21st IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2022), November 28-30, Ginowan, Japan, Pages 472-479, IEEE, 2022.

  8. Zhongjie Yu; Fabrizio Ventola; Kristian Kersting

    Whittle Networks: A Deep Likelihood Model for Time Series

    In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2021), July 18-24, Pages 12177-12186, Proceedings of Machine Learning Research, Vol. 139, PMLR, 2021.

  9. Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations

    In: IEEE Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June 19-25, Pages 3619-3629, Computer Vision Foundation / IEEE, 2021.

  10. Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

    In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Conference on Artificial Intelligence (AAAI-2021), Pages 9533-9540, AAAI Press, 2021.

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