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Guest editorial: special issue on machine learning for soccer.

D. Berrar, P. Lopes, J. Davis, and W. Dubitzky. Machine Learning, 108 (1): 1-7 (2019)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Dr. -Ing. Daniel Holder University of Stuttgart

Optimisation Approach for the Convergence Process of Design and Technology in Automotive DevelopmentF. Reichelt, D. Holder, and T. Maier. Interdisciplinary Practice in Industrial Design : Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, 100, page 109-118. New York, AHFE Open Access, (2023)

Daniel Holder University of Stuttgart

Daniel Sollich University of Stuttgart

Daniel Mezger University of Stuttgart

Univ. -Prof. Dr. Daniel Hole University of Stuttgart

Other publications of authors with the same name

On the Noise Resilience of Ranking Measures.D. Berrar. ICONIP (2), volume 9948 of Lecture Notes in Computer Science, page 47-55. (2016)Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers.D. Berrar. Machine Learning, 106 (6): 911-949 (2017)Incorporating domain knowledge in machine learning for soccer outcome prediction.D. Berrar, P. Lopes, and W. Dubitzky. Machine Learning, 108 (1): 97-126 (2019)SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data Streams.C. Wiwatcharakoses, and D. Berrar. Expert Syst. Appl., (2020)Self-Organizing Incremental Neural Networks for Continual Learning.C. Wiwatcharakoses, and D. Berrar. IJCAI, page 6476-6477. ijcai.org, (2019)Guest editorial: special issue on machine learning for soccer.D. Berrar, P. Lopes, J. Davis, and W. Dubitzky. Machine Learning, 108 (1): 1-7 (2019)The Open International Soccer Database for machine learning.W. Dubitzky, P. Lopes, J. Davis, and D. Berrar. Machine Learning, 108 (1): 9-28 (2019)Should significance testing be abandoned in machine learning?D. Berrar, and W. Dubitzky. Int. J. Data Sci. Anal., 7 (4): 247-257 (2019)Learning from automatically labeled data: case study on click fraud prediction.D. Berrar. Knowl. Inf. Syst., 46 (2): 477-490 (2016)Detecting click fraud in online advertising: a data mining approach.R. Oentaryo, E. Lim, M. Finegold, D. Lo, F. Zhu, C. Phua, E. Cheu, G. Yap, K. Sim, M. Nguyen and 8 other author(s). J. Mach. Learn. Res., 15 (1): 99-140 (2014)