87 citations · 157 across the 9 of their papers we have counts for
9 papers
FLGo: A Fully Customizable Federated Learning Platform
Zheng Wang, Xiaoliang Fan, Zhaopeng Peng +6
Federated learning (FL) has found numerous applications in healthcare, finance, and IoT scenarios. Many existing FL frameworks offer a range of benchmarks to evaluate the performan…
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
Chuanpan Zheng, Xiaoliang Fan, Cheng Wang +3
Spatio-temporal kriging is an important problem in web and social applications, such as Web or Internet of Things, where things (e.g., sensors) connected into a web often come with…
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability
Zheng Wang, Xiaoliang Fan, Jianzhong Qi +4
While federated learning has shown strong results in optimizing a machine learning model without direct access to the original data, its performance may be hindered by intermittent…
Multi-Graph Fusion Networks for Urban Region Embedding
Shangbin Wu, Xu Yan, Xiaoliang Fan +5
Learning the embeddings for urban regions from human mobility data can reveal the functionality of regions, and then enables the correlated but distinct tasks such as crime predict…
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting
Chuanpan Zheng, Xiaoliang Fan, Shirui Pan +5
Recent studies have shifted their focus towards formulating traffic forecasting as a spatio-temporal graph modeling problem. Typically, they constructed a static spatial graph at e…
ConTIG: Continuous Representation Learning on Temporal Interaction Graphs
Xu Yan, Xiaoliang Fan, Peizhen Yang +5
Representation learning on temporal interaction graphs (TIG) is to model complex networks with the dynamic evolution of interactions arising in a broad spectrum of problems. Existi…
Federated Learning with Fair Averaging
Zheng Wang, Xiaoliang Fan, Jianzhong Qi +3
Fairness has emerged as a critical problem in federated learning (FL). In this work, we identify a cause of unfairness in FL -- conflicting gradients with large differences in the…
iTV: Inferring Traffic Violation-Prone Locations with Vehicle Trajectories and Road Environment Data
Zhihan Jiang, Longbiao Chen, Binbin Zhou +4
Traffic violations like illegal parking, illegal turning, and speeding have become one of the greatest challenges in urban transportation systems, bringing potential risks of traff…
GMAN: A Graph Multi-Attention Network for Traffic Prediction
Chuanpan Zheng, Xiaoliang Fan, Cheng Wang +1
Long-term traffic prediction is highly challenging due to the complexity of traffic systems and the constantly changing nature of many impacting factors. In this paper, we focus on…