Journal Papers

Lieck, Robert and Marc Toussaint (2016). “Temporally Extended Features in Model-Based Reinforcement Learning with Partial Observability”. In: Neurocomputing 192, pp. 49–60.
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Stefan K. Saevarsson, Gulshan B. Sharma, Heiko Ramm, Robert Lieck, Carol R. Hutchison, Jason Werle, Sigrun Matthiasdottir, Spencer J. Montgomery, Carolina I. Romeo, Stefan Zachow, and Carolyn Anglin (2013). “Kinematic Differences Between Gender Specific and Traditional Knee Implants”. In: The Journal of Arthroplasty 28.9, pp. 1543–1550.
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Ho, K. C. T., S. K. Saevarsson, H. Ramm, R. Lieck, S. Zachow, G. B. Sharma, E. L. Rex, S. Amiri, B. C. Y. Wu, A. Leumann, and C. Anglin (2012). “Computed Tomography Analysis of Knee Pose and Geometry before and after Total Knee Arthroplasty”. In: Journal of Biomechanics 45.13, pp. 2215–2221.
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Saevarsson, Stefan, Gulshan Sharma, Shahram Amiri, Sigrun Montgomery, Heiko Ramm, Derek Lichti, Robert Lieck, Stefan Zachow, and Carolyn Anglin (2012). “Radiological Method for Measuring Patellofemoral Tracking and Tibiofemoral Kinematics before and after Total Knee Replacement”. In: Bone and Joint Research 1.10, pp. 263–271.

Conference Papers

Landsnes, Kristoffer, Liana Mehrabyan, Victor Wiklund, Fabian C Moss, Robert Lieck, and Martin Rohrmeier (2019). “A Model Comparison for Chord Prediction on the Annotated Beethoven Corpus”. In: Proceedings of the 16th Sound & Music Computing Conference. 16th Sound & Music Computing Conference, p. 4.
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Langhabel, Jonas, Robert Lieck, Marc Toussaint, and Martin Rohrmeier (2017). “Feature Discovery for Sequential Prediction of Monophonic Music”. In: Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR). International Society for Music Information Retrieval Conference.
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Lieck, Robert and Marc Toussaint (2015). “Discovering Temporally Extended Features for Reinforcement Learning in Domains with Delayed Causalities”. In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Presses universitaires de Louvain, p. 183.
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Saevarsson, Stefan, Gulshan Sharma, Sigrun Montgomery, Karen Ho, Heiko Ramm, Robert Lieck, Stefan Zachow, Carol Hutchison, Jason Werle, and Carolyn Anglin (2012). “Kinematic Comparison Between Gender Specific and Traditional Femoral Implants”. In: 67th Canadian Orthopaedic Association (COA) Annual Meeting.

Sharma, Gulshan, Karen Ho, Stefan Saevarsson, Heiko Ramm, Robert Lieck, Stefan Zachow, and Carolyn Anglin (2012). “Knee Pose and Geometry Pre- and Post-Total Knee Arthroplasty Using Computed Tomography”. In: 58th Annual Meeting of the Orthopaedic Research Society (ORS).

Saevarsson, Stefan, Gulshan B. Sharma, Spencer J. Montgomery, Karen Ho, Heiko Ramm, Robert Lieck, Stefan Zachow, and Carolyn Anglin (2011). “Kinematic Comparison Between Gender Specific and Traditional Femoral Implants”. In: Proceedings of the 11th Alberta Biomedical Engineering (BME) Conference (Poster), p. 80.

Workshop Contributions & Technical Reports

Charisi, Vicky, Louise Dennis, Michael Fisher, Robert Lieck, Andreas Matthias, Marija Slavkovik, Janina Sombetzki, Alan FT Winfield, and Roman Yampolskiy (2017). Towards Moral Autonomous Systems.
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Lieck, Robert, Vien Ngo, and Marc Toussaint (2017). “Exploiting Variance Information in Monte-Carlo Tree Search”. In: ICAPS Workshop on Heuristics and Search for Domain-Independent Planning.
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Lieck, Robert and Marc Toussaint (2017). “Active Tree Search”. In: ICAPS Workshop on Planning, Search, and Optimization.
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Kulick, Johannes, Robert Lieck, and Marc Toussaint (2016). “Cross-Entropy as a Criterion for Robust Interactive Learning of Latent Properties”. In: NIPS Workshop on the Future of Interactive Learning Machines.
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Kulick, Johannes, Robert Lieck, and Marc Toussaint (2014a). Active Learning of Hyperparameters: An Expected Cross Entropy Criterion for Active Model Selection. arXiv.
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Kulick, Johannes, Robert Lieck, and Marc Toussaint (2014b). The Advantage of Cross Entropy over Entropy in Iterative Information Gathering. arXiv 1409.7552. University of Stuttgart.
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PhD Thesis

Lieck, Robert (2018). “Learning Structured Models for Active Planning: Beyond the Markov Paradigm Towards Adaptable Abstractions”. PhD thesis. Universitšt Stuttgart.
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Other

Lieck, Robert, Harasim Daniel, and Martin Rohrmeier (2018a). “Learning Structured Models of Musical Syntax”.
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Lieck, Robert, Harasim Daniel, and Martin Rohrmeier (2018b). “Towards a Unified Model for Harmony and Voice-Leading”.
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Lieck, Robert (2014). “Temporally Extended Features: Modeling Delayed Causalities in Reinforcement Learning”.
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