3 papers
cs.LG2026
FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching
Haoran Zhang, Cainã Figueiredo Pereira, Marie Siew +3
Federated learning (FL) is often subject to aggregation variance if clients do not consistently participate in training rounds. While reusing stale model updates from inactive clie…
cs.LG2025
Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems
Binquan Guo, Junteng Cao, Marie Siew +3
Large-scale low-Earth-orbit (LEO) satellite systems are increasingly valued for their ability to enable rapid and wide-area data exchange, thereby facilitating the collaborative tr…
cs.LG2025
Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC)
Nan Li, Wanting Yang, Marie Siew +4
Diffusion models (DMs) have emerged as powerful tools for high-quality content generation, yet their intensive computational requirements for inference pose challenges for resource…