3 citations · 5 across the 9 of their papers we have counts for
9 papers
LAFA: Agentic LLM-Driven Federated Analytics over Decentralized Data Sources
Haichao Ji, Zibo Wang, Cheng Pan +4
Large Language Models (LLMs) have shown great promise in automating data analytics tasks by interpreting natural language queries and generating multi-operation execution plans. Ho…
B2LoRa: Boosting LoRa Transmission for Satellite-IoT Systems with Blind Coherent Combining
Yimin Zhao, Weibo Wang, Xiong Wang +6
With the rapid growth of Low Earth Orbit (LEO) satellite networks, satellite-IoT systems using the LoRa technique have been increasingly deployed to provide widespread Internet ser…
Towards Real-Time Neural Volumetric Rendering on Mobile Devices: A Measurement Study
Zhe Wang, Yifei Zhu
Neural Radiance Fields (NeRF) is an emerging technique to synthesize 3D objects from 2D images with a wide range of potential applications. However, rendering existing NeRF models…
A Survey on Federated Analytics: Taxonomy, Enabling Techniques, Applications and Open Issues
Zibo Wang, Haichao Ji, Yifei Zhu +2
The escalating influx of data generated by networked edge devices, coupled with the growing awareness of data privacy, has restricted the traditional data analytics workflow, where…
Federated Analytics-Empowered Frequent Pattern Mining for Decentralized Web 3.0 Applications
Zibo Wang, Yifei Zhu, Dan Wang +1
The emerging Web 3.0 paradigm aims to decentralize existing web services, enabling desirable properties such as transparency, incentives, and privacy preservation. However, current…
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service
Yu Liu, Zibo Wang, Yifei Zhu +1
Federated learning (FL) has emerged as a prevalent distributed machine learning scheme that enables collaborative model training without aggregating raw data. Cloud service provide…
FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks
Qiying Pan, Ruofan Wu, Tengfei Liu +3
Federated training of Graph Neural Networks (GNN) has become popular in recent years due to its ability to perform graph-related tasks under data isolation scenarios while preservi…
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices
Qiying Pan, Yifei Zhu, Lingyang Chu
Graph neural networks (GNN) have been widely deployed in real-world networked applications and systems due to their capability to handle graph-structured data. However, the growing…
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy
Qiying Pan, Yifei Zhu
Node embedding aims to map nodes in the complex graph into low-dimensional representations. The real-world large-scale graphs and difficulties of labeling motivate wide studies of…