4 papers
Scalable and Reliable Over-the-Air Federated Edge Learning
Maximilian Egger, Christoph Hofmeister, Cem Kaya +2
Federated edge learning (FEEL) has emerged as a core paradigm for large-scale optimization. However, FEEL still suffers from a communication bottleneck due to the transmission of h…
Maximal-Capacity Discrete Memoryless Channel Identification
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh +2
The problem of identifying the channel with the highest capacity among several discrete memoryless channels (DMCs) is considered. The problem is cast as a pure-exploration multi-ar…
Sparsity and Privacy in Secret Sharing: A Fundamental Trade-Off
Rawad Bitar, Maximilian Egger, Antonia Wachter-Zeh +1
This work investigates the design of sparse secret sharing schemes that encode a sparse private matrix into sparse shares. This investigation is motivated by distributed computing,…
Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load
Maximilian Egger, Serge Kas Hanna, Rawad Bitar
In distributed machine learning, a central node outsources computationally expensive calculations to external worker nodes. The properties of optimization procedures like stochasti…