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9900 Publications
2021 | Conference Paper | LibreCat-ID: 48286
Habernal, I. (2021). When differential privacy meets NLP: The devil is in the detail. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. https://doi.org/10.18653/v1/2021.emnlp-main.114
LibreCat
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2021 | Conference Paper | LibreCat-ID: 29893
Rehlaender, P., Unruh, R., Schafmeister, F., & Böcker, J. (2021). Alternating Asymmetrical Phase-Shift Modulation for Full-Bridge Converters with Balanced Switching Losses to Reduce Thermal Imbalances. 2021 IEEE Applied Power Electronics Conference and Exposition (APEC). 2021 IEEE Applied Power Electronics Conference and Exposition (APEC), Phoenix, AZ, USA. https://doi.org/10.1109/apec42165.2021.9487104
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2021 | Journal Article | LibreCat-ID: 34827
Bruns, J., Unterhauser, E., & Gasteiger, H. (2021). Geometrisches Begriffsverständnis in der Grundschule am Beispiel der Begriffe Viereck, Rechteck und Quadrat. Journal für Mathematik-Didaktik, 42(2), 581–623. https://doi.org/10.1007/s13138-021-00185-4
LibreCat
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2021 | Journal Article | LibreCat-ID: 45382
Prediger, S., & Dröse, J. (2021). Fehlerbearbeitung bei mathematischen Textaufgaben – Sprachliche und strategische Fehlerursachen und ihre Bearbeitung. Lernen und Lernstörungen, 10(2). https://doi.org/doi.org/10.1024/2235-0977/a000330
LibreCat
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2021 | Conference Paper | LibreCat-ID: 26770 | 
von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., & Haeb-Umbach, R. (2021). Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation of Arbitrary Numbers of Speakers. Interspeech 2021. Interspeech. https://doi.org/10.21437/interspeech.2021-1177
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2021 | Conference Paper | LibreCat-ID: 29173 |
von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., & Haeb-Umbach, R. (2021). Speeding Up Permutation Invariant Training for Source Separation. Speech Communication; 14th ITG Conference. Speech Communication; 14th ITG Conference, Kiel.
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2021 | Conference Paper | LibreCat-ID: 29308 |
Ebbers, J., & Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments. Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021), 226–230.
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2021 | Conference Paper | LibreCat-ID: 29306 |
Ebbers, J., Keyser, M. C., & Haeb-Umbach, R. (2021). Adapting Sound Recognition to A New Environment Via Self-Training. Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 1135–1139.
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2021 | Journal Article | LibreCat-ID: 24456 |
Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., & Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717–728. https://doi.org/10.1109/tcds.2020.3044366
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2021 | Conference Paper | LibreCat-ID: 48853
Bossek, J., Neumann, A., & Neumann, F. (2021). Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference, 556–564. https://doi.org/10.1145/3449639.3459364
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48855
Bossek, J., Neumann, A., & Neumann, F. (2021). Exact Counting and~Sampling of Optima for the Knapsack Problem. Learning and Intelligent Optimization, 40–54. https://doi.org/10.1007/978-3-030-92121-7_4
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48860
Bossek, J., & Neumann, F. (2021). Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 198–206. https://doi.org/10.1145/3449639.3459363
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2021 | Book Chapter | LibreCat-ID: 48862
Bossek, J., & Sudholt, D. (2021). Do Additional Optima Speed up Evolutionary Algorithms? In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (pp. 1–11). Association for Computing Machinery.
LibreCat
2021 | Book Chapter | LibreCat-ID: 48881
Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (pp. 1–15). Association for Computing Machinery.
LibreCat
2021 | Conference Paper | LibreCat-ID: 48876
Bossek, J., & Wagner, M. (2021). Generating Instances with Performance Differences for More than Just Two Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1423–1432. https://doi.org/10.1145/3449726.3463165
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2021 | Conference Paper | LibreCat-ID: 48893
Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 600–608. https://doi.org/10.1145/3449639.3459384
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48891
Neumann, A., Bossek, J., & Neumann, F. (2021). Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions. Proceedings of the Genetic and Evolutionary Computation Conference, 261–269. https://doi.org/10.1145/3449639.3459385
LibreCat
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2021 | Book Chapter | LibreCat-ID: 48892
Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation. In Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms (pp. 1–11). Association for Computing Machinery.
LibreCat
2021 | Journal Article | LibreCat-ID: 48854
Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2021). Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica, 83(10), 3148–3179. https://doi.org/10.1007/s00453-021-00838-3
LibreCat
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2021 | Journal Article | LibreCat-ID: 25212
Qudus, U., Saleem, M., Ngonga Ngomo, A.-C., & Lee, Y.-K. (n.d.). An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines. Semantic Web, 12(6), 843–868. https://doi.org/10.3233/SW-200420
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