25 citations · 33 across the 3 of their papers we have counts for
3 papers
A Privacy Preserving System for Movie Recommendations Using Federated Learning
David Neumann, Andreas Lutz, Karsten Müller +1
Recommender systems have become ubiquitous in the past years. They solve the tyranny of choice problem faced by many users, and are utilized by many online businesses to drive enga…
FedAUXfdp: Differentially Private One-Shot Federated Distillation
Haley Hoech, Roman Rischke, Karsten Müller +1
Federated learning suffers in the case of non-iid local datasets, i.e., when the distributions of the clients' data are heterogeneous. One promising approach to this challenge is t…
ECQ: Explainability-Driven Quantization for Low-Bit and Sparse DNNs
Daniel Becking, Maximilian Dreyer, Wojciech Samek +2
The remarkable success of deep neural networks (DNNs) in various applications is accompanied by a significant increase in network parameters and arithmetic operations. Such increas…