190 citations · 247 across the 11 of their papers we have counts for
11 papers
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
Zhenxiao Zhang, Zhidong Gao, Yuanxiong Guo +1
Motivated by the drawbacks of cloud-based federated learning (FL), cooperative federated edge learning (CFEL) has been proposed to improve efficiency for FL over mobile edge networ…
Quantum-Assisted Joint Caching and Power Allocation for Integrated Satellite-Terrestrial Networks
Yu Zhang, Yanmin Gong, Lei Fan +3
Low earth orbit (LEO) satellite network can complement terrestrial networks for achieving global wireless coverage and improving delay-sensitive Internet services. This paper propo…
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy
Zhenxiao Zhang, Yuanxiong Guo, Yuguang Fang +1
Federated Learning (FL) is a collaborative learning framework that enables edge devices to collaboratively learn a global model while keeping raw data locally. Although FL avoids l…
Scalable and Low-Latency Federated Learning with Cooperative Mobile Edge Networking
Zhenxiao Zhang, Zhidong Gao, Yuanxiong Guo +1
Federated learning (FL) enables collaborative model training without centralizing data. However, the traditional FL framework is cloud-based and suffers from high communication lat…
Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy
Rui Hu, Yanmin Gong, Yuanxiong Guo
Federated learning (FL) that enables edge devices to collaboratively learn a shared model while keeping their training data locally has received great attention recently and can pr…
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization
Rui Hu, Yanmin Gong, Yuanxiong Guo
Federated learning (FL) enables distributed agents to collaboratively learn a centralized model without sharing their raw data with each other. However, data locality does not prov…
Differentially Private Federated Learning for Resource-Constrained Internet of Things
Rui Hu, Yuanxiong Guo, E. Paul. Ratazzi +1
With the proliferation of smart devices having built-in sensors, Internet connectivity, and programmable computation capability in the era of Internet of things (IoT), tremendous d…
Concentrated Differentially Private and Utility Preserving Federated Learning
Rui Hu, Yuanxiong Guo, Yanmin Gong
Federated learning is a machine learning setting where a set of edge devices collaboratively train a model under the orchestration of a central server without sharing their local d…
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy
Zonghao Huang, Rui Hu, Yuanxiong Guo +2
Alternating Direction Method of Multipliers (ADMM) is a widely used tool for machine learning in distributed settings, where a machine learning model is trained over distributed da…
Smart Charging and Parking of Plug-in Hybrid Electric Vehicles in Microgrids Considering Renewable Energy Sources
Zheming Liang, Yuanxiong Guo
With the current trend of transforming a centralized power system into a decentralized one for efficiency, reliability, and environment reasons, the concept of microgrid that integ…
Aggregation-Based Datacenter Energy Management in Wholesale Electricity Markets
Zhe Yu, Yuanxiong Guo, Miao Pan +1
In this paper, we study how datacenter energy cost can be effectively reduced in the wholesale electricity market via cooperative power procurement. Intuitively, by aggregating wor…