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Scene-Conditioned Relation Routing for urban cellular activity forecasting
Qingzhong Li, Jingye Lin, Hui Ma +4
Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and call activity. Existing methods…
Multimodal Spatiotemporal-Frequency Fusion with Peak Enhancement for Cellular Traffic Forecasting
Qingzhong Li, Yue Hu, Hui Ma +4
Accurate forecasting of cellular network traffic is essential for network planning, resource allocation, and quality-of-service assurance in modern mobile communication systems. Re…
FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting
Qingzhong Li, Yue Hu, Zhou Long +3
Accurate and up-to-date forecasting of the power grid's carbon footprint is crucial for effective product carbon footprint (PCF) accounting and informed decarbonization decisions.…
Sim-MSTNet: sim2real based Multi-task SpatioTemporal Network Traffic Forecasting
Hui Ma, Qingzhong Li, Jin Wang +4
Network traffic forecasting plays a crucial role in intelligent network operations, but existing techniques often perform poorly when faced with limited data. Additionally, multi-t…
Multi-dimensional Fair Federated Learning
Cong Su, Guoxian Yu, Jun Wang +3
Federated learning (FL) has emerged as a promising collaborative and secure paradigm for training a model from decentralized data without compromising privacy. Group fairness and c…