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Manuel Fritz
Manuel Fritz
Data Analytics @ Zeiss SMT
Verified email at ipvs.uni-stuttgart.de - Homepage
Title
Cited by
Cited by
Year
AutoML4Clust: Efficient AutoML for Clustering Analyses
D Tschechlov, M Fritz, H Schwarz
Proceedings of the 24th International Conference on Extending Database …, 2021
202021
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
182020
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
112019
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
92020
Initializing k-means efficiently: Benefits for exploratory cluster analysis
M Fritz, H Schwarz
On the Move to Meaningful Internet Systems: OTM 2019 Conferences …, 2019
62019
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
52023
Benchmarking big data technologies for energy procurement efficiency
M Fritz, S Albrecht, H Ziekow, J Strüker
52017
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
42022
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
42020
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
42020
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
32022
Efficient Exploratory Clustering Analyses with Qualitative Approximations
M Fritz, D Tschechlov, H Schwarz
Proceedings of the 24th International Conference on Extending Database …, 2021
32021
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
32017
Automatic Selection of Analytic Platforms with ASAP-DM
M Fritz, G Shao, H Schwarz
Proceedings of the 33rd International Conference on Scientific and …, 2021
12021
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
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