1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.DC2024★ 1 cited
Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices
Shengyuan Ye, Liekang Zeng, Xiaowen Chu +2
On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-preserving machine learning at the edge. However, the intensive training workload and limite…
cs.DC2024
Resource-Efficient Personal Large Language Models Fine-Tuning with Collaborative Edge Computing
Shengyuan Ye, Bei Ouyang, Tianyi Qian +6
Large language models (LLMs) have unlocked a plethora of powerful applications at the network edge, such as intelligent personal assistants. Data privacy and security concerns have…
cs.NI2024
Design and Optimization of Hierarchical Gradient Coding for Distributed Learning at Edge Devices
Weiheng Tang, Jingyi Li, Lin Chen +1
Edge computing has recently emerged as a promising paradigm to boost the performance of distributed learning by leveraging the distributed resources at edge nodes. Architecturally,…