activity
20222026
most citedDecentralized Collaborative Learning Framework for Next POI Recommendation

5 citations · 17 across the 27 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.LG2024

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.…

cs.IR2024★ 1 cited

Harnessing Large Language Models for Group POI Recommendations

Jing Long, Liang Qu, Junliang Yu +3

The rapid proliferation of Location-Based Social Networks (LBSNs) has underscored the importance of Point-of-Interest (POI) recommendation systems in enhancing user experiences. Wh…

cs.IR2024★ 2 cited

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…

cs.IR2024

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…

cs.IR2024★ 1 cited

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…

cs.LG2024

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…