Author

Maximilian Andreas Hoefler

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Preprint Aug 2026

A Privacy Study of Sparse Collaborative Inference

It is concluded that the positions of sparse activations should be treated as sensitive transmitted data and audited carefully in the context of collaborative inference, and that sparsification reduces the leakage far less than it reduces the transmission cost.

Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek · 0 citations

Jul 2026

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning

FedKT-CSD (Federated Knowledge Transfer via Collaborative Synthetic Data), a framework inspired by neural image compression that closes the gap in jointly achieving low communication, robustness to heterogeneity, and rigorous privacy by leveraging publicly pretrained autoencoders as a shared latent space.

Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek · arXiv.org · 0 citations