Manuel Fritz

Orcid: 0000-0003-4640-8477

According to our database1, Manuel Fritz authored at least 15 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis.
Proc. ACM Manag. Data, 2023

2022
Efficient exploratory clustering analyses in large-scale exploration processes.
VLDB J., 2022

DATA-IMP: An Interactive Approach to Specify Data Imputation Transformations on Large Datasets.
Proceedings of the Cooperative Information Systems - 28th International Conference, 2022

2021
Methods for enhanced exploratory clustering analyses.
PhD thesis, 2021

Automatic Selection of Analytic Platforms with ASAP-DM.
Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

AutoML4Clust: Efficient AutoML for Clustering Analyses.
Proceedings of the 24th International Conference on Extending Database Technology, 2021

Efficient Exploratory Clustering Analyses with Qualitative Approximations.
Proceedings of the 24th International Conference on Extending Database Technology, 2021

2020
LOG-Means: Efficiently Estimating the Number of Clusters in Large Datasets.
Proc. VLDB Endow., 2020

ASAP-DM: a framework for automatic selection of analytic platforms for data mining.
SICS Softw.-Intensive Cyber Phys. Syst., 2020

Learning from Past Observations: Meta-Learning for Efficient Clustering Analyses.
Proceedings of the Big Data Analytics and Knowledge Discovery, 2020

Empowering Domain Experts to Preprocess Massive Distributed Datasets.
Proceedings of the Business Information Systems - 23rd International Conference, 2020

2019
Quality-driven early stopping for explorative cluster analysis for big data.
SICS Softw.-Intensive Cyber Phys. Syst., 2019

Initializing k-Means Efficiently: Benefits for Exploratory Cluster Analysis.
Proceedings of the On the Move to Meaningful Internet Systems: OTM 2019 Conferences, 2019

2017
Targeting customers for an optimized energy procurement.
Comput. Sci. Res. Dev., 2017

Benchmarking Big Data Technologies for Energy Procurement Efficiency.
Proceedings of the 23rd Americas Conference on Information Systems, 2017


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