3 papers
cs.LG2026
A Privacy Study of Sparse Collaborative Inference
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek
Collaborative inference (CI) splits a model between an edge device and a server, whereby the client computes an intermediate activation, transmits it, and the server completes the…
cs.LG2026
Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek
One-shot federated learning (OSFL) addresses the communication overhead of federated learning by limiting training to a single round, but doing so without sacrificing model quality…
cs.LG2026
FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek
Explainable AI (XAI) methods have demonstrated significant success in recent years at identifying relevant features in input data that drive deep learning model decisions, enhancin…