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26 Publications
2023 | Journal Article | LibreCat-ID: 46310
Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2023). A study on the effects of normalized TSP features for automated algorithm selection. Theoretical Computer Science, 940, 123–145. https://doi.org/10.1016/j.tcs.2022.10.019
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2021 | Conference Paper | LibreCat-ID: 27652
Aimiyekagbon, O. K., Bender, A., & Sextro, W. (2021). Extraktion und Selektion geeigneter Merkmale für die Restlebensdauerprognose von technischen Systemen trotz aleatorischen Unsicherheiten . VDI-Berichte 2391, 197–210.
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2021 | Conference Paper | LibreCat-ID: 22507 | 
Aimiyekagbon, O. K., Bender, A., & Sextro, W. (n.d.). On the applicability of time series features as health indicators for technical systems operating under varying conditions. Proceedings of the Seventeenth International Conference on Condition Monitoring and Asset Management (CM 2021). Seventeenth International Conference on Condition Monitoring and Asset Management (CM 2021).
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2021 | Conference Paper | LibreCat-ID: 27111 |
Aimiyekagbon, O. K., Muth, L., Wohlleben, M. C., Bender, A., & Sextro, W. (2021). Rule-based Diagnostics of a Production Line. In P. Do, S. King, & O. Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021 (Vol. 6, Issue 1, pp. 527–536). https://doi.org/10.36001/phme.2021.v6i1.3042
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2020 | Conference Paper | LibreCat-ID: 16933 |
Gottschalk, S., Rittmeier, F., & Engels, G. (2020). Hypothesis-driven Adaptation of Business Models based on Product Line Engineering. In Proceedings of the 22nd IEEE International Conference on Business Informatics. Antwerp: IEEE. https://doi.org/10.1109/CBI49978.2020.00022
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, M., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. https://doi.org/10.1007/978-3-030-58112-1_4
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2019 | Conference Paper | LibreCat-ID: 15488
Thiel, C., Steidl, C., & Henning, B. (2019). P2.9 Comparison of deep feature extraction techniques for varying-length time series from an industrial piercing press. In AMA Service GmbH (Ed.), 20. GMA/ITG-Fachtagung. Sensoren und Messsysteme 2019. Von-Münchhausen-Str. 49, 31515 Wunstorf. https://doi.org/10.5162/SENSOREN2019/P2.9
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2019 | Conference Paper | LibreCat-ID: 13138 |
Gottschalk, S., Rittmeier, F., & Engels, G. (2019). Intertwined Development of Business Model and Product Functions for Mobile Applications: A Twin Peak Feature Modeling Approach. In S. Hyrynsalmi, M. Suoranta, A. Nguyen-Duc, P. Tyrväinen, & P. Abrahamsson (Eds.), Software Business (Vol. 370, pp. 192–207). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-33742-1_16
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2018 | Journal Article | LibreCat-ID: 2331
Kim, Y., Lee, S., Dollmann, M., & Geierhos, M. (2018). Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure. International Journal of Advanced Science and Technology, 112, 123–136. https://doi.org/10.14257/ijast.2018.112.12
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2016 | Conference Paper | LibreCat-ID: 15873
Boschmann, A., Agne, A., Witschen, L. M., Thombansen, G., Kraus, F., & Platzner, M. (2016). FPGA-based acceleration of high density myoelectric signal processing. In 2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig). Mexiko City, Mexiko: IEEE. https://doi.org/10.1109/reconfig.2015.7393312
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2016 | Conference Paper | LibreCat-ID: 48873
Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization (pp. 48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
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2015 | Conference Paper | LibreCat-ID: 11813 |
Heymann, J., Haeb-Umbach, R., Golik, P., & Schlueter, R. (2015). Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions. In Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on (pp. 5053–5057). https://doi.org/10.1109/ICASSP.2015.7178933
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2014 | Conference Paper | LibreCat-ID: 9880
Kimotho, J. K., & Sextro, W. (2014). An approach for feature extraction and selection from non-trending data for machinery prognosis. In Proceedings of the Second European Conference of the Prognostics and Health Management Society 2014 (Vol. 5).
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2014 | Journal Article | LibreCat-ID: 11861
Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2014). A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22(1), 95–109. https://doi.org/10.1109/TASLP.2013.2285480
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2013 | Conference Paper | LibreCat-ID: 11716
Abdelaziz, A. H., Zeiler, S., Kolossa, D., Leutnant, V., & Haeb-Umbach, R. (2013). GMM-based significance decoding. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 6827–6831). https://doi.org/10.1109/ICASSP.2013.6638984
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2013 | Journal Article | LibreCat-ID: 11862
Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2013). Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 21(8), 1640–1652. https://doi.org/10.1109/TASL.2013.2258013
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2013 | Conference Paper | LibreCat-ID: 46388
Nallaperuma, S., Wagner, M., Neumann, F., Bischl, B., Mersmann, O., & Trautmann, H. (2013). A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem. Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII, 147–160. https://doi.org/10.1145/2460239.2460253
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2013 | Journal Article | LibreCat-ID: 48889
Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem. Annals of Mathematics and Artificial Intelligence, 69(2), 151–182. https://doi.org/10.1007/s10472-013-9341-2
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2012 | Conference Paper | LibreCat-ID: 11864 |
Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2012). A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR. In Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on.
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2012 | Conference Paper | LibreCat-ID: 48890
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219, 115–129.
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