10 citations · 18 across the 7 of their papers we have counts for
5 papers · 1 filter
Collaborative Synthetic Data for Privacy-Preserving Financial Fraud Detection Across Organizational Silos
Simeon Allmendinger, Domenique Zipperling, Burhanettin Bahadir Kibar +2
Organizations seek analytical value from AI, yet relevant data are often fragmented across organizations and constrained by privacy. This is acute in financial fraud detection, whe…
A Multivocal Literature Review on Privacy and Fairness in Federated Learning
Beatrice Balbierer, Lukas Heinlein, Domenique Zipperling +1
Federated Learning presents a way to revolutionize AI applications by eliminating the necessity for data sharing. Yet, research has shown that information can still be extracted du…
CollaFuse: Collaborative Diffusion Models
Simeon Allmendinger, Domenique Zipperling, Lukas Struppek +1
In the landscape of generative artificial intelligence, diffusion-based models have emerged as a promising method for generating synthetic images. However, the application of diffu…
CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AI
Domenique Zipperling, Simeon Allmendinger, Lukas Struppek +1
In the landscape of generative artificial intelligence, diffusion-based models present challenges for socio-technical systems in data requirements and privacy. Traditional approach…
A review of systematic selection of clustering algorithms and their evaluation
Marc Wegmann, Domenique Zipperling, Jonas Hillenbrand +1
Data analysis plays an indispensable role for value creation in industry. Cluster analysis in this context is able to explore given datasets with little or no prior knowledge and t…