25 citations · 56 across the 23 of their papers we have counts for
8 papers · 1 filter
A Trust-Network-Based Federated Learning Framework for Multi-Center Aging Clock Prediction
Chunxu Zhang, Bo Li, Wenliang Wang +7
Aging clocks quantify biological aging and help characterize individual health status. What protein interactions are important for accurate aging clocks, and are they zeroth-order…
FedDis: A Causal Disentanglement Framework for Federated Traffic Prediction
Chengyang Zhou, Zijian Zhang, Chunxu Zhang +4
Federated learning offers a promising paradigm for privacy-preserving traffic prediction, yet its performance is often challenged by the non-identically and independently distribut…
TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting
Mingyuan Xia, Chunxu Zhang, Zijian Zhang +4
Temporal non-stationarity, the phenomenon that time series distributions change over time, poses fundamental challenges to reliable time series forecasting. Intuitively, the comple…
Distilling A Universal Expert from Clustered Federated Learning
Zeqi Leng, Chunxu Zhang, Guodong Long +2
Clustered Federated Learning (CFL) addresses the challenges posed by non-IID data by training multiple group- or cluster-specific expert models. However, existing methods often ove…
Incomplete Graph Learning: A Comprehensive Survey
Riting Xia, Huibo Liu, Anchen Li +4
Graph learning is a prevalent field that operates on ubiquitous graph data. Effective graph learning methods can extract valuable information from graphs. However, these methods ar…
AutoSTL: Automated Spatio-Temporal Multi-Task Learning
Zijian Zhang, Xiangyu Zhao, Hao Miao +3
Spatio-Temporal prediction plays a critical role in smart city construction. Jointly modeling multiple spatio-temporal tasks can further promote an intelligent city life by integra…
Curvature Regularization to Prevent Distortion in Graph Embedding
Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang +2
Recent research on graph embedding has achieved success in various applications. Most graph embedding methods preserve the proximity in a graph into a manifold in an embedding spac…
Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks
Chunxu Zhang, Jiaxu Cui, Bo Yang
In recent years, deep learning has achieved remarkable achievements in many fields, including computer vision, natural language processing, speech recognition and others. Adequate…