论文成果
[see full list from: Google Scholar]
[1] Yi Zhao, Yanyan Shen, Junjie Yao. Recurrent Neural Network for Text Classification with Hierarchical Multiscale Dense Connections. In IJCAI, 2019.
[2] Yanan Xu, Yanmin Zhu, Yanyan Shen, Jiadi Yu. Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation. In IJCAI, 2019.
[3] Weiyu Cheng, Yanyan Shen, Linpeng Huang, Yanmin Zhu. Incorporating Interpretability into Latent Factor Models via Fast Infuence Analysis. In KDD, 2019. (research track, oral)
[4] Shimin Di, Yanyan Shen, Lei Chen. Relation Extraction via Domain-aware Transfer Learning. In KDD, 2019. (research track, oral)
[5] Yi Zhao, Yanyan Shen, Yanmin Zhu, Junjie Yao. Forecasting Wavelet Transformed Time Series with Attentive Neural Networks. In ICDM, 2018.
[6] Ranzhen Li, Yanyan Shen, Yanmin Zhu. Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention. In ICDM, 2018.
[7] Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang. DELF: A Dual-Embedding based Deep Latent Factor Model for Recommendation. In IJCAI, 2018.
[8] Yanyan Shen, Jinyang Gao. Refine or Represent: Residual Networks with Explicit Channel-wise Configuration. In IJCAI, 2018.
[9] Zhaoyang Liu, Yanyan Shen, Yanmin Zhu. Where Will Dockless Shared Bikes be Stacked? -- Parking Hotspots Detection in a New City. In KDD, 2018. (oral)
[10] Shimin Di, Jingshu Peng, Yanyan Shen, Lei Chen. Transfer Learning via Feature Isomorphism Discovery. In KDD, 2018.
[11] Bowen Zhang, Yanyan Shen, Yanmin Zhu, Jiadi Yu. A GPU-accelerated Framework for Processing Trajectory Queries. In ICDE, 2018.
[12] Xian Zhou, Yanyan Shen, Yanmin Zhu, Linpeng Huang. Predicting Multi-step Citywide Passenger Demands using Attention-based Neural Networks. In WSDM, pages 736-744, 2018.
[13] Zhaoyang Liu, Yanyan Shen, Yanmin Zhu. Inferring Dockless Shared Bike Distribution in New Cities. In WSDM, pages 378-386, 2018.
[14] Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang. A Neural Attention Model for Urban Air Quality Inference: Learning the Weights of Monitoring Stations. In AAAI, 2018.
