15 citations · 18 across the 2 of their papers we have counts for
4 papers
Scaling Federated Learning for Fine-tuning of Large Language Models
Agrin Hilmkil, Sebastian Callh, Matteo Barbieri +3
Federated learning (FL) is a promising approach to distributed compute, as well as distributed data, and provides a level of privacy and compliance to legal frameworks. This makes…
Specialized federated learning using a mixture of experts
Edvin Listo Zec, Olof Mogren, John Martinsson +2
In federated learning, clients share a global model that has been trained on decentralized local client data. Although federated learning shows significant promise as a key approac…
Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks
Leon René Sütfeld, Flemming Brieger, Holger Finger +2
The most widely used activation functions in current deep feed-forward neural networks are rectified linear units (ReLU), and many alternatives have been successfully applied, as w…
Human decisions in moral dilemmas are largely described by Utilitarianism: virtual car driving study provides guidelines for ADVs
Maximilian Alexander Wächter, Anja Faulhaber, Felix Blind +6
Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in a utilitarian way, trying to cause as little over…