Dennis Treder-Tschechlov

According to our database, Dennis Treder-Tschechlov authored at least 10 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Exploiting domain knowledge to address class imbalance and a heterogeneous feature space in multi-class classification.

Vitali Hirsch, Peter Reimann, Dennis Treder-Tschechlov, Holger Schwarz, Bernhard Mitschang

VLDB J., September, 2023

ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis.

Dennis Treder-Tschechlov, Manuel Fritz, Holger Schwarz, Bernhard Mitschang

Proc. ACM Manag. Data, 2023

SDRank: A Deep Learning Approach for Similarity Ranking of Data Sources to Support User-Centric Data Analysis.

Michael Behringer, Dennis Treder-Tschechlov, Julius Voggesberger, Pascal Hirmer, Bernhard Mitschang

Proceedings of the 25th International Conference on Enterprise Information Systems, 2023

Approach to Synthetic Data Generation for Imbalanced Multi-class Problems with Heterogeneous Groups.

Dennis Treder-Tschechlov, Peter Reimann, Holger Schwarz, Bernhard Mitschang

Proceedings of the Datenbanksysteme für Business, 2023

2022

Efficient exploratory clustering analyses in large-scale exploration processes.

Manuel Fritz, Michael Behringer, Dennis Tschechlov, Holger Schwarz

VLDB J., 2022

Increasing Explainability of Clustering Results for Domain Experts by Identifying Meaningful Features.

Michael Behringer, Pascal Hirmer, Dennis Tschechlov, Bernhard Mitschang

Proceedings of the 24th International Conference on Enterprise Information Systems, 2022

2021

AutoML4Clust: Efficient AutoML for Clustering Analyses.

Dennis Tschechlov, Manuel Fritz, Holger Schwarz

Proceedings of the 24th International Conference on Extending Database Technology, 2021

Efficient Exploratory Clustering Analyses with Qualitative Approximations.

Manuel Fritz, Dennis Tschechlov, Holger Schwarz

Proceedings of the 24th International Conference on Extending Database Technology, 2021

2020

Learning from Past Observations: Meta-Learning for Efficient Clustering Analyses.

Manuel Fritz, Dennis Tschechlov, Holger Schwarz

Proceedings of the Big Data Analytics and Knowledge Discovery, 2020

2019

Towards a Collaborative Repository for the Documentation of Service-Based Antipatterns and Bad Smells.

Justus Bogner, Tobias Boceck, Matthias Popp, Dennis Tschechlov, Stefan Wagner, Alfred Zimmermann

Proceedings of the IEEE International Conference on Software Architecture Companion, 2019