3 papers
cs.CR2026
Model Multiplicity for Adversarial Detection in Small Language Model Training on Edge Devices
Stefan Behfar, Richard Mortier
The rise of edge-based machine learning has enabled distributed adaptation of language models across mobile and IoT devices, offering privacy preservation and real-time responsiven…
cs.DC2026
Robust Synchronisation for Federated Learning in The Face of Correlated Device Failure
Stefan Behfar, Richard Mortier
Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of participating nodes per round.…
cs.DC2024
FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications
Grant Wilkins, Sheng Di, Jon C. Calhoun +5
With the promise of federated learning (FL) to allow for geographically-distributed and highly personalized services, the efficient exchange of model updates between clients and se…