1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
SoK: Assessing the State of Applied Federated Machine Learning
Tobias Müller, Maximilian Stäbler, Hugo Gascón +2
Machine Learning (ML) has shown significant potential in various applications; however, its adoption in privacy-critical domains has been limited due to concerns about data privacy…
cs.AI2023★ 1 cited
Unlocking the Potential of Collaborative AI -- On the Socio-technical Challenges of Federated Machine Learning
Tobias Müller, Milena Zahn, Florian Matthes
The disruptive potential of AI systems roots in the emergence of big data. Yet, a significant portion is scattered and locked in data silos, leaving its potential untapped. Federat…