249 citations · 1.2k across the 42 of their papers we have counts for
5 papers · 1 filter
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Bing Luo, Wenli Xiao, Shiqiang Wang +2
Federated learning (FL) algorithms usually sample a fraction of clients in each round (partial participation) when the number of participants is large and the server's communicatio…
Cost-Effective Federated Learning in Mobile Edge Networks
Bing Luo, Xiang Li, Shiqiang Wang +2
Federated learning (FL) is a distributed learning paradigm that enables a large number of mobile devices to collaboratively learn a model under the coordination of a central server…
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning
Anirban Das, Timothy Castiglia, Shiqiang Wang +1
We consider federated learning in tiered communication networks. Our network model consists of a set of silos, each holding a vertical partition of the data. Each silo contains a h…
Communication-efficient k-Means for Edge-based Machine Learning
Hanlin Lu, Ting He, Shiqiang Wang +5
We consider the problem of computing the k-means centers for a large high-dimensional dataset in the context of edge-based machine learning, where data sources offload machine lear…
Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System
Yiwen Han, Shihao Shen, Xiaofei Wang +2
Kubernetes (k8s) has the potential to merge the distributed edge and the cloud but lacks a scheduling framework specifically for edge-cloud systems. Besides, the hierarchical distr…