25 citations · 56 across the 23 of their papers we have counts for
5 papers · 1 filter
PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
Zijian Zhang, Xiangyu Zhao, Qidong Liu +6
In the era of information explosion, spatio-temporal data mining serves as a critical part of urban management. Considering the various fields demanding attention, e.g., traffic st…
When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions
Chunxu Zhang, Guodong Long, Tianyi Zhou +3
Federated recommendation system usually trains a global model on the server without direct access to users' private data on their own devices. However, this separation of the recom…
GPFedRec: Graph-guided Personalization for Federated Recommendation
Chunxu Zhang, Guodong Long, Tianyi Zhou +3
The federated recommendation system is an emerging AI service architecture that provides recommendation services in a privacy-preserving manner. Using user-relation graphs to enhan…
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…
Dual Personalization on Federated Recommendation
Chunxu Zhang, Guodong Long, Tianyi Zhou +4
Federated recommendation is a new Internet service architecture that aims to provide privacy-preserving recommendation services in federated settings. Existing solutions are used t…