62 citations · 274 across the 31 of their papers we have counts for
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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.LG2018★ 2 cited
Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach
Ahmed Elnaggar, Robin Otto, Florian Matthes
In the legal domain it is important to differentiate between words in general, and afterwards to link the occurrences of the same entities. The topic to solve these challenges is c…