AutoML4Clust: Efficient AutoML for Clustering Analyses D Tschechlov, M Fritz, H Schwarz Proceedings of the 24th International Conference on Extending Database …, 2021 | 20 | 2021 |
LOG-Means: Efficiently Estimating the Number of Clusters in Large Datasets M Fritz, M Behringer, H Schwarz Proceedings of the VLDB Endowment 13 (11), 2020 | 18 | 2020 |
Quality-driven early stopping for explorative cluster analysis for big data M Fritz, M Behringer, H Schwarz SICS Software-Intensive Cyber-Physical Systems 34, 129-140, 2019 | 11 | 2019 |
Empowering domain experts to preprocess massive distributed datasets M Behringer, P Hirmer, M Fritz, B Mitschang Business Information Systems: 23rd International Conference, BIS 2020 …, 2020 | 9 | 2020 |
Initializing k-means efficiently: Benefits for exploratory cluster analysis M Fritz, H Schwarz On the Move to Meaningful Internet Systems: OTM 2019 Conferences …, 2019 | 6 | 2019 |
ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis D Treder-Tschechlov, M Fritz, H Schwarz, B Mitschang Proceedings of the ACM on Management of Data 1 (2), 1-26, 2023 | 5 | 2023 |
Benchmarking big data technologies for energy procurement efficiency M Fritz, S Albrecht, H Ziekow, J Strüker | 5 | 2017 |
Efficient exploratory clustering analyses in large-scale exploration processes M Fritz, M Behringer, D Tschechlov, H Schwarz The VLDB Journal 31 (4), 711-732, 2022 | 4 | 2022 |
ASAP-DM: a framework for automatic selection of analytic platforms for data mining M Fritz, O Muazzen, M Behringer, H Schwarz SICS Software-Intensive Cyber-Physical Systems 35, 17-29, 2020 | 4 | 2020 |
Learning from past observations: Meta-learning for efficient clustering analyses M Fritz, D Tschechlov, H Schwarz Big Data Analytics and Knowledge Discovery: 22nd International Conference …, 2020 | 4 | 2020 |
DATA-IMP: An Interactive Approach to Specify Data Imputation Transformations on Large Datasets M Behringer, M Fritz, H Schwarz, B Mitschang International Conference on Cooperative Information Systems, 55-74, 2022 | 3 | 2022 |
Efficient Exploratory Clustering Analyses with Qualitative Approximations M Fritz, D Tschechlov, H Schwarz Proceedings of the 24th International Conference on Extending Database …, 2021 | 3 | 2021 |
Targeting customers for an optimized energy procurement: A Cost Segmentation Based on Smart Meter Load Profiles S Albrecht, M Fritz, J Strüker, H Ziekow Computer Science-Research and Development 32, 225-235, 2017 | 3 | 2017 |
Automatic Selection of Analytic Platforms with ASAP-DM M Fritz, G Shao, H Schwarz Proceedings of the 33rd International Conference on Scientific and …, 2021 | 1 | 2021 |
Ensemble Clustering Based on Meta-Learning and Hyperparameter Optimization D Treder-Tschechlov, M Fritz, H Schwarz, B Mitschang Proceedings of the VLDB Endowment 17 (11), 2880-2892, 2024 | | 2024 |
Empowering Domain Experts to Enhance Clustering Results Through Interactive Refinement}} M Behringer, D Treder-Tschechlov, J Rapp, D Treder-Tschechlov, M Fritz, ... Onizuka, M., et al. Database Systems for Advanced Applications. DASFAA 2024 …, 2024 | | 2024 |
Methods for enhanced exploratory clustering analyses M Fritz | | 2021 |
Energieinformatik mit Big Data Technologien M Frey-Luxemburger, M Fritz, H Ziekow | | 2017 |