4 papers
ACPSL: Adaptive Communication-Computation Pipeline Parallel Split Learning over Edge Networks
Chenyu Liu, Zhaoyang Zhang, Zirui Chen +3
In wireless edge networks, split learning (SL) enables base station (BS) to utilize the distributed data and computing power across user equipments (UEs) to achieve collaborative m…
Gradient Compression May Hurt Generalization: A Remedy by Synthetic Data Guided Sharpness Aware Minimization
Yujie Gu, Richeng Jin, Zhaoyang Zhang +1
It is commonly believed that gradient compression in federated learning (FL) enjoys significant improvement in communication efficiency with negligible performance degradation. In…
TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data
Richeng Jin, Yujie Gu, Kai Yue +3
Distributed training of deep neural networks faces three critical challenges: privacy preservation, communication efficiency, and robustness to fault and adversarial behaviors. Alt…
An Edge-Cloud Collaboration Framework for Generative AI Service Provision with Synergetic Big Cloud Model and Small Edge Models
Yuqing Tian, Zhaoyang Zhang, Yuzhi Yang +5
Generative artificial intelligence (GenAI) offers various services to users through content creation, which is believed to be one of the most important components in future network…