249 citations · 1.2k across the 42 of their papers we have counts for
5 papers · 1 filter
Model Pruning Enables Efficient Federated Learning on Edge Devices
Yuang Jiang, Shiqiang Wang, Victor Valls +4
Federated learning (FL) allows model training from local data collected by edge/mobile devices while preserving data privacy, which has wide applicability to image and vision appli…
Distilling On-Device Intelligence at the Network Edge
Jihong Park, Shiqiang Wang, Anis Elgabli +6
Devices at the edge of wireless networks are the last mile data sources for machine learning (ML). As opposed to traditional ready-made public datasets, these user-generated privat…
Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
Stephen Pasteris, Shiqiang Wang, Mark Herbster +1
Mobile edge computing (MEC) is a promising technique for providing low-latency access to services at the network edge. The services are hosted at various types of edge nodes with b…
Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems
Tiffany Tuor, Shiqiang Wang, Kin K. Leung +1
Large-scale distributed computing systems often contain thousands of distributed nodes (machines). Monitoring the conditions of these nodes is important for system management purpo…
Robust Coreset Construction for Distributed Machine Learning
Hanlin Lu, Ming-Ju Li, Ting He +3
Coreset, which is a summary of the original dataset in the form of a small weighted set in the same sample space, provides a promising approach to enable machine learning over dist…