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2184 Publications
2018 | Journal Article | LibreCat-ID: 16924
Harteis, C., Kok, E., & Jarodzka, H. (2018). The journey to proficiency: Exploring new objective methodologies to capture the process of learning and professional development. . Frontline Learning Research, 6(3), 1–5.
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2018 | Conference Paper | LibreCat-ID: 1061
Gutt, D. (2018). Sorting Out the Lemons - Identifying Product Failures in Online Reviews and their Relationship with Sales. In Proceedings of the Multikonferenz Wirtschaftsinformatik 2018 (MKWI), Lüneburg, Germany.
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2018 | Conference Paper | LibreCat-ID: 11712
El Baff, R., Wachsmuth, H., Al Khatib, K., & Stein, B. (2018). Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus. In Proceedings of the 22nd Conference on Computational Natural Language Learning (pp. 454–464). Association for Computational Linguistics.
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2018 | Conference Paper | LibreCat-ID: 11760 | 
Ebbers, J., Nelus, A., Martin, R., & Haeb-Umbach, R. (2018). Evaluation of Modulation-MFCC Features and DNN Classification for Acoustic Event Detection. In DAGA 2018, München.
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2018 | Conference Paper | LibreCat-ID: 11872 |
Drude, L., Boeddeker, C., Heymann, J., Kinoshita, K., Delcroix, M., Nakatani, T., & Haeb-Umbach, R. (2018). Integration neural network based beamforming and weighted prediction error dereverberation. In INTERSPEECH 2018, Hyderabad, India.
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2018 | Bachelorsthesis | LibreCat-ID: 1188
Kempf, J. (2018). Learning deterministic bandit behaviour form compositions. Universität Paderborn.
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2018 | Journal Article | LibreCat-ID: 11916 |
Despotovic, V., Walter, O., & Haeb-Umbach, R. (2018). Machine learning techniques for semantic analysis of dysarthric speech: An experimental study. Speech Communication 99 (2018) 242-251 (Elsevier B.V.).
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2018 | Conference Paper | LibreCat-ID: 12900 |
Drude, L., Higuchi, Takuya , Kinoshita, K., Nakatani, T., & Haeb-Umbach, R. (2018). Dual Frequency- and Block-Permutation Alignment for Deep Learning Based Block-Online Blind Source Separation. In ICASSP 2018, Calgary, Canada.
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2018 | Conference Paper | LibreCat-ID: 15584
Magenheim, J., Müller, K., Schulte, C., Bergner, N., Haselmeier, K., Humbert, L., … Schroeder, U. (2018). Evaluation of Learning Informatics in Primary Education - Views of Teachers and Students. In Informatics in Schools. Fundamentals of Computer Science and Software Engineering - 11th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, (ISSEP) 2018, St. Petersburg, Russia, October 10-12, 2018, Proceedings (pp. 339–353). https://doi.org/10.1007/978-3-030-02750-6\_26
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2018 | Conference Paper | LibreCat-ID: 15585
Bednarik, R., Schulte, C., Budde, L., Heinemann, B., & Vrzakova, H. (2018). Eye-movement Modeling Examples in Source Code Comprehension: A Classroom Study. In Proceedings of the 18th Koli Calling International Conference on Computing Education Research, Koli, Finland, November 22-25, 2018 (pp. 2:1-2:8). https://doi.org/10.1145/3279720.3279722
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2018 | Book | LibreCat-ID: 15595
Sentance, S., Barendsen, E., & Schulte, C. (2018). Computer Science Education: Perspectives on Teaching and learning in school. Bloomsbury Publishing.
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2018 | Journal Article | LibreCat-ID: 14887
Chen, M.-H., Chen, W.-F., & Ku, L.-W. (2018). Application of Sentiment Analysis to Language Learning. IEEE Access, 6, 24433–24442.
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2018 | Journal Article | LibreCat-ID: 16038
Schäfer, D., & Hüllermeier, E. (2018). Dyad ranking using Plackett-Luce models based on joint feature representations. Machine Learning, 107(5), 903–941.
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2018 | Preprint | LibreCat-ID: 16293 |
Klus, S., Peitz, S., & Schuster, I. (2018). Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. ArXiv:1805.10118.
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2018 | Conference Paper | LibreCat-ID: 10145
Ahmadi Fahandar, M., & Hüllermeier, E. (2018). Learning to Rank Based on Analogical Reasoning. In Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI) (pp. 2951–2958).
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2018 | Conference Paper | LibreCat-ID: 10148
El Mesaoudi-Paul, A., Hüllermeier, E., & Busa-Fekete, R. (2018). Ranking Distributions based on Noisy Sorting. Proc. 35th Int. Conference on Machine Learning (ICML), 3469–3477.
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2018 | Conference Paper | LibreCat-ID: 10149
Hesse, M., Timmermann, J., Hüllermeier, E., & Trächtler, A. (2018). A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart. Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20.
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2018 | Book Chapter | LibreCat-ID: 10152
Mencia, E. L., Fürnkranz, J., Hüllermeier, E., & Rapp, M. (2018). Learning interpretable rules for multi-label classification. In H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, & M. A. J. van Gerven (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning (pp. 81–113). Springer.
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2018 | Conference Paper | LibreCat-ID: 10184
Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning Using Dyad Ranking. Proc. 21st Int. Conference on Discovery Science (DS), 161–175.
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2018 | Journal Article | LibreCat-ID: 10276
Schäfer, D., & Hüllermeier, E. (2018). Dyad Ranking Using Plackett-Luce Models based on joint feature representations. Machine Learning, 107(5), 903–941.
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