arxiv
PublishedMay 27, 2026 at 4:00 AM
—neutral
On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach
Publisher summary· verbatim
arXiv:2605.26162v1 Announce Type: cross Abstract: Asynchronous decentralized federated learning (ADFL) eliminates central coordination and global synchronization, making it attractive for large-scale and heterogeneous systems. However, frequent peer-to-peer communication, asynchronous updates on dir
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning2harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning2harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models2harxivTemporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents2hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗