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2021
Fritz, M., Behringer, M., Tschechlov, D, and Schwarz, H. 2021. "Efficient exploratory clustering analyses in large-scale exploration processes". The VLDB Journal (2021).
Tschechlov, D., Fritz, M., and Schwarz, H. 2021. “AutoML4Clust: Efficient AutoML for Clustering Analyses,” in Proceedings of the International Conference on Extending Database Technology (EDBT 2021).
Fritz, M., Tschechlov, D., and Schwarz, H. 2021. “Efficient Exploratory Clustering Analyses with Qualitative Approximations,” in Proceedings of the International Conference on Extending Database Technology (EDBT 2021).
2020
Fritz, M., Tschechlov, D., and Schwarz, H. 2020. “Learning from past observations: Meta-Learning for Efficient Clustering Analyses,” in Proceedings of 22nd International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2020). Lecture Notes in Computer Science (Vol. 12393 LNCS), Springer, Cham, pp. 364-379.
2019
Tschechlov, D. (2019). Analysis and Transfer of AutoML Concepts for Clustering Algorithms (Master's thesis). http://dx.doi.org/10.18419/opus-10755.
J. Bogner, T. Boceck, M. Popp, D. Tschechlov, S. Wagner and A. Zimmermann, "Towards a Collaborative Repository for the Documentation of Service-Based Antipatterns and Bad Smells," 2019 IEEE International Conference on Software Architecture Companion (ICSA-C), 2019, pp. 95-101, doi: 10.1109/ICSA-C.2019.00025.