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Publications

Displaying results 471 to 480 of 682.

  1. Jason Raphael Rambach

    Learning Priors for Augmented Reality Tracking and Scene Understanding

    PhD-Thesis, Technische Universität Kaiserslautern, ISBN 978-3-8439-4555-4, Dr.Hut, München, 9/2020.

  2. Marcel Heinz; Jakob Michael Schönborn; Klaus-Dieter Althoff

    Development and Implementation of a Case-Based Reasoning Approach to Speed-Up Deep Reinforcement Learning through Case-Injection for AI Gameplay

    In: Daniel Trabold; Pascal Welke; Nico Piatkowski (Hrsg.). Lernen, Wissen, Daten, Analysen. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" (LWDA-2020), September 9-11, Online, Pages 142-153, CEUR, 2020.

  3. Marco Schreyer; Timur Sattarov; Damian Borth; Andreas Dengel; Bernd Reimer

    Künstliche Intelligenz in der Wirtschaftsprüfung - Identifikation ungewöhnlicher Buchungen in der Finanzbuchhaltung

    In: Die Wirtschaftsprüfung (WPg), Vol. 71, Pages 674-681, IDW Verlag, 6/2018.

  4. Max Leimkühler; Laura Gravemeier; Tim Biester; Oliver Thomas

    Deep learning object detection as an assistance system for complex image labeling tasks

    In: Proceedings of the 54th Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences (HICSS-2021), A Virtual AIS Conference, located at 54th, January 5-8, Hawaii, Hawaii, USA, ISBN 978-0-9981331-4-0, AIS, 2021.

  5. Nijat Mehdiyev

    Explainable Process Predictions (xPP): A Holistic Framework and Applications

    In: Claudio Di Ciccio; Benoît Depaire; Jochen De Weerdt; Chiara Di Francescomarino; Jorge Munoz-Gama (Hrsg.). ICPM 2020. International Conference on Process Mining (ICPM-2020), 2nd, October 4-9, Padua, Italy, Pages 17-18, Vol. 2703, CEUR, 2020.

  6. Nijat Mehdiyev; Peter Fettke

    Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring

    In: Witold Pedrycz; Shyi-Ming Chen (Hrsg.). Interpretable Artificial Intelligence: A Perspective of Granular Computing. Chapter 1, Pages 1-28, Vol. 937, ISBN 9783030649487, Springer, 2021.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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