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443 Publications


2021 | Working Paper | LibreCat-ID: 45616
van Straaten, Dirk, et al. Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes. 2021.
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2021 | Journal Article | LibreCat-ID: 24456 | OA
Rohlfing, Katharina J., et al. “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems.” IEEE Transactions on Cognitive and Developmental Systems, vol. 13, no. 3, 2021, pp. 717–28, doi:10.1109/tcds.2020.3044366.
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2020 | Preprint | LibreCat-ID: 19603 | OA
Bode, Henrik, et al. “Towards a Scalable and Flexible Simulation and Testing Environment  Toolbox for Intelligent Microgrid Control.” ArXiv:2005.04869, 2020.
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2020 | Conference Paper | LibreCat-ID: 19953 | OA
Damke, Clemens, et al. “A Novel Higher-Order Weisfeiler-Lehman Graph Convolution.” Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020), edited by Sinno Jialin Pan and Masashi Sugiyama, vol. 129, PMLR, 2020, pp. 49–64.
LibreCat | Files available | arXiv
 

2020 | Preprint | LibreCat-ID: 20211 | OA
Lienen, Julian, and Eyke Hüllermeier. “Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce  Model.” ArXiv:2010.13118, 2020.
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2020 | Conference Paper | LibreCat-ID: 24146
Heid, Stefan Helmut, et al. “Constrained Multi-Agent Optimization with Unbounded Information Delay.” Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020, vol. 26, 2020, p. 247.
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2020 | Conference Paper | LibreCat-ID: 17407
Tornede, Alexander, et al. “Extreme Algorithm Selection with Dyadic Feature Representation.” Discovery Science, 2020.
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2020 | Conference Paper | LibreCat-ID: 17408
Hanselle, Jonas Manuel, et al. “Hybrid Ranking and Regression for Algorithm Selection.” KI 2020: Advances in Artificial Intelligence, 2020.
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2020 | Conference Paper | LibreCat-ID: 17424
Tornede, Tanja, et al. “AutoML for Predictive Maintenance: One Tool to RUL Them All.” Proceedings of the ECMLPKDD 2020, 2020, doi:10.1007/978-3-030-66770-2_8.
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2020 | Preprint | LibreCat-ID: 17605 | OA
Heid, Stefan Helmut, et al. “Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction.” Journal of Data Mining and Digital Humanities, episciences.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede, Alexander, et al. “Towards Meta-Algorithm Selection.” Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
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2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul, Adil, et al. “Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach.” Learning and Intelligent Optimization. LION 2020., vol. 12096, Springer, 2020, pp. 216–32, doi:10.1007/978-3-030-53552-0_22.
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2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul, Adil, et al. “Online Preselection with Context Information under the Plackett-Luce  Model.” ArXiv:2002.04275.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede, Alexander, et al. “Run2Survive: A Decision-Theoretic Approach to Algorithm Selection Based on Survival Analysis.” ACML 2020, 2020.
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2020 | Journal Article | LibreCat-ID: 16725
Richter, Cedric, et al. “Algorithm Selection for Software Validation Based on Graph Kernels.” Journal of Automated Software Engineering, Springer.
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2020 | Conference Paper | LibreCat-ID: 15629
Wever, Marcel Dominik, et al. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. Springer.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label Classification. 2019.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne, V. K., et al. “Choice Functions Generated by Mallows and Plackett–Luce Relations.” New Mathematics and Natural Computation, vol. 15, no. 2, 2019, pp. 191–213.
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2019 | Journal Article | LibreCat-ID: 15001
Couso, Ines, et al. “Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning.” IEEE Computational Intelligence Magazine, 2019, pp. 31–44, doi:10.1109/mci.2018.2881642.
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2019 | Journal Article | LibreCat-ID: 15002 | OA
Waegeman, Willem, et al. “Multi-Target Prediction: A Unifying View on Problems and Methods.” Data Mining and Knowledge Discovery, vol. 33, no. 2, 2019, pp. 293–324, doi:10.1007/s10618-018-0595-5.
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