3 papers
cs.DC2025
Distributed Bilevel Optimization with Dual Pruning for Resource-limited Clients
Mingyi Li, Xiao Zhang, Ruisheng Zheng +4
With the development of large-scale models, traditional distributed bilevel optimization algorithms cannot be applied directly in low-resource clients. The key reason lies in the e…
cs.LG2025
Data-Free Continual Learning of Server Models in Model-Heterogeneous Cloud-Device Collaboration
Xiao Zhang, Zengzhe Chen, Yuan Yuan +5
The rise of cloud-device collaborative computing has enabled intelligent services to be delivered across distributed edge devices while leveraging centralized cloud resources. In t…
cs.DC2025
Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients
Yan Li, Xiao Zhang, Mingyi Li +7
In this work, we study to release the potential of massive heterogeneous weak computing power to collaboratively train large-scale models on dispersed datasets. In order to improve…