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Deep Subdomain Adaptation Network for Image Classification
Yongchun Zhu, Fuzhen Zhuang, Jindong Wang +5
For a target task where labeled data is unavailable, domain adaptation can transfer a learner from a different source domain. Previous deep domain adaptation methods mainly learn a…
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning
Weijia Zhang, Hao Liu, Fan Wang +4
Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability. However, in many large cities, EV drive…
Out-of-Town Recommendation with Travel Intention Modeling
Haoran Xin, Xinjiang Lu, Tong Xu +4
Out-of-town recommendation is designed for those users who leave their home-town areas and visit the areas they have never been to before. It is challenging to recommend Point-of-I…
CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendation
Carter Blum, Hao Liu, Hui Xiong
Electric vehicles have been rapidly increasing in usage, but stations to charge them have not always kept up with demand, so efficient routing of vehicles to stations is critical t…
Spatial Object Recommendation with Hints: When Spatial Granularity Matters
Hui Luo, Jingbo Zhou, Zhifeng Bao +5
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularit…
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks
Jindong Han, Hao Liu, Hengshu Zhu +2
Accurate and timely air quality and weather predictions are of great importance to urban governance and human livelihood. Though many efforts have been made for air quality or weat…