40 citations · 71 across the 21 of their papers we have counts for
22 papers
Tackling Data Heterogeneity in Federated Time Series Forecasting
Wei Yuan, Guanhua Ye, Xiangyu Zhao +3
Time series forecasting plays a critical role in various real-world applications, including energy consumption prediction, disease transmission monitoring, and weather forecasting.…
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
Hechuan Wen, Tong Chen, Guanhua Ye +3
Causal effect estimation (CEE) provides a crucial tool for predicting the unobserved counterfactual outcome for an entity. As CEE relaxes the requirement for ``perfect'' counterfac…
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
Xinyi Gao, Yayong Li, Tong Chen +3
With the increasing computation of training graph neural networks (GNNs) on large-scale graphs, graph condensation (GC) has emerged as a promising solution to synthesize a compact,…
On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective
Hung Vinh Tran, Tong Chen, Guanhua Ye +3
Content-based Recommender Systems (CRSs) play a crucial role in shaping user experiences in e-commerce, online advertising, and personalized recommendations. However, due to the va…
DecKG: Decentralized Collaborative Learning with Knowledge Graph Enhancement for POI Recommendation
Ruiqi Zheng, Liang Qu, Guanhua Ye +3
Decentralized collaborative learning for Point-of-Interest (POI) recommendation has gained research interest due to its advantages in privacy preservation and efficiency, as it kee…
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services
Wei Yuan, Chaoqun Yang, Guanhua Ye +3
Federated sequential recommendation (FedSeqRec) has gained growing attention due to its ability to protect user privacy. Unfortunately, the performance of FedSeqRec is still unsati…
Physics-guided Active Sample Reweighting for Urban Flow Prediction
Wei Jiang, Tong Chen, Guanhua Ye +4
Urban flow prediction is a spatio-temporal modeling task that estimates the throughput of transportation services like buses, taxis, and ride-sharing, where data-driven models have…
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender System
Wei Yuan, Chaoqun Yang, Liang Qu +3
Sequential recommender systems have made significant progress. Recently, due to increasing concerns about user data privacy, some researchers have implemented federated learning fo…
Poisoning Attacks and Defenses in Recommender Systems: A Survey
Zongwei Wang, Junliang Yu, Min Gao +4
Modern recommender systems (RS) have profoundly enhanced user experience across digital platforms, yet they face significant threats from poisoning attacks. These attacks, aimed at…
RobGC: Towards Robust Graph Condensation
Xinyi Gao, Hongzhi Yin, Tong Chen +3
Graph neural networks (GNNs) have attracted widespread attention for their impressive capability of graph representation learning. However, the increasing prevalence of large-scale…
Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations
Jing Long, Guanhua Ye, Tong Chen +3
The rapid expansion of Location-Based Social Networks (LBSNs) has highlighted the importance of effective next Point-of-Interest (POI) recommendations, which leverage historical ch…
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition
Xinyi Gao, Guanhua Ye, Tong Chen +3
The increasing prevalence of large-scale graphs poses a significant challenge for graph neural network training, attributed to their substantial computational requirements. In resp…
Robust Federated Contrastive Recommender System against Model Poisoning Attack
Wei Yuan, Chaoqun Yang, Liang Qu +3
Federated Recommender Systems (FedRecs) have garnered increasing attention recently, thanks to their privacy-preserving benefits. However, the decentralized and open characteristic…
Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation
Jing Long, Tong Chen, Guanhua Ye +3
As an indispensable personalized service within Location-Based Social Networks (LBSNs), the Point-of-Interest (POI) recommendation aims to assist individuals in discovering attract…
Graph Condensation: A Survey
Xinyi Gao, Junliang Yu, Tong Chen +3
The rapid growth of graph data poses significant challenges in storage, transmission, and particularly the training of graph neural networks (GNNs). To address these challenges, gr…
Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion
Lijian Chen, Wei Yuan, Tong Chen +3
Visually-aware recommender systems have found widespread application in domains where visual elements significantly contribute to the inference of users' potential preferences. Whi…
Unraveling the "Anomaly" in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution
Yuting Sun, Guansong Pang, Guanhua Ye +3
The ongoing challenges in time series anomaly detection (TSAD), notably the scarcity of anomaly labels and the variability in anomaly lengths and shapes, have led to the need for a…
Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation
Guanhua Ye, Tong Chen, Quoc Viet Hung Nguyen +1
As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model, personalized IoT service providers ha…
Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation
Guanhua Ye, Tong Chen, Yawen Li +3
In this paper, we propose a Similarity-Quality-based Messenger Distillation (SQMD) framework for heterogeneous asynchronous on-device healthcare analytics. By introducing a preload…
Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent
Guanhua Ye, Hongzhi Yin, Tong Chen +3
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learn…
FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection
Guanhua Ye, Hongzhi Yin, Tong Chen +3
Obstructive Sleep Apnea (OSA) is a highly prevalent but inconspicuous disease that seriously jeopardizes the health of human beings. Polysomnography (PSG), the gold standard of det…
Try This Instead: Personalized and Interpretable Substitute Recommendation
Tong Chen, Hongzhi Yin, Guanhua Ye +3
As a fundamental yet significant process in personalized recommendation, candidate generation and suggestion effectively help users spot the most suitable items for them. Consequen…