485 citations
- Tsinghua UniversityCN18 papers
- Chinese Academy of SciencesCN16 papers
- University of Chinese Academy of SciencesCN14 papers
- Institute of High Energy PhysicsCN10 papers
- Peking UniversityCN10 papers
- Institute of Theoretical PhysicsCN6 papers
- The University of TokyoJP5 papers
- Chongqing UniversityCN4 papers
- Inner Mongolia UniversityCN4 papers
- Jilin UniversityCN4 papers
- Ministry of Agriculture and Rural AffairsCN4 papers
- Nanyang Technological UniversitySG4 papers
9 papers · 1 filter
CausalPOI: Spatio-Temporal Graph-Based Causal Modeling for Cold-Start POI Check-in Forecasting
Zhaoqi Zhang, Miao Xie, Yi Li +3
As urban environments continue to evolve rapidly, accurately modeling the dynamic behaviour of Points of Interest is essential for supporting data-driven urban planning and commerc…
Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising
Zhaoqi Zhang, Jiaming Deng, Miao Xie +5
Guaranteed display advertising is crucial for platform monetization, yet existing methods often operate under a single-slot assumption, limiting their ability to optimize allocatio…
Novel clustered federated learning based on local loss
Endong Gu, Yongxin Chen, Hao Wen +2
This paper proposes LCFL, a novel clustering metric for evaluating clients' data distributions in federated learning. LCFL aligns with federated learning requirements, accurately a…
Integrated Decision and Control at Multi-Lane Intersections with Mixed Traffic Flow
Jianhua Jiang, Yangang Ren, Yang Guan +3
Autonomous driving at intersections is one of the most complicated and accident-prone traffic scenarios, especially with mixed traffic participants such as vehicles, bicycles and p…
Unified Framework for Feature Extraction based on Contrastive Learning
Hongjie Zhang
Feature extraction is an efficient approach for alleviating the issue of dimensionality in high-dimensional data. As a popular self-supervised learning method, contrastive learning…
Principal Component Analysis Based on T-norm Maximization
Xiang-Fei Yang, Yuan-Hai Shao, Chun-Na Li +2
Classical principal component analysis (PCA) may suffer from the sensitivity to outliers and noise. Therefore PCA based on -norm and -norm () have been s…