39 citations · 77 across the 14 of their papers we have counts for
4 papers · 1 filter
Scalable Data Point Valuation in Decentralized Learning
Konstantin D. Pandl, Chun-Yin Huang, Ivan Beschastnikh +3
Existing research on data valuation in federated and swarm learning focuses on valuing client contributions and works best when data across clients is independent and identically d…
Reward Systems for Trustworthy Medical Federated Learning
Konstantin D. Pandl, Florian Leiser, Scott Thiebes +1
Federated learning (FL) has received high interest from researchers and practitioners to train machine learning (ML) models for healthcare. Ensuring the trustworthiness of these mo…
Practitioner Motives to Use Different Hyperparameter Optimization Methods
Niclas Kannengießer, Niklas Hasebrook, Felix Morsbach +5
Programmatic hyperparameter optimization (HPO) methods, such as Bayesian optimization and evolutionary algorithms, are highly sample-efficient in identifying optimal hyperparameter…
Architecture Matters: Investigating the Influence of Differential Privacy on Neural Network Design
Felix Morsbach, Tobias Dehling, Ali Sunyaev
One barrier to more widespread adoption of differentially private neural networks is the entailed accuracy loss. To address this issue, the relationship between neural network arch…