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cs.IT2025
LoByITFL: Low Communication Secure and Private Federated Learning
Yue Xia, Maximilian Egger, Christoph Hofmeister +1
Privacy of the clients' data and security against Byzantine clients are key challenges in Federated Learning (FL). Existing solutions to joint privacy and security incur sacrifices…
cs.IT2025
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises
Yue Xia, Christoph Hofmeister, Maximilian Egger +1
Federated learning (FL) shows great promise in large scale machine learning, but brings new risks in terms of privacy and security. We propose ByITFL, a novel scheme for FL that pr…
cs.IT2025
Multi-Terminal Remote Generation and Estimation Over a Broadcast Channel With Correlated Priors
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh +2
We study the multi-terminal remote estimation problem under a rate constraint, in which the goal of the encoder is to help each decoder estimate a function over a certain distribut…