| Cdas: a crowdsourcing data analytics system X Liu, M Lu, BC Ooi, Y Shen, S Wu, M Zhang Proceedings of the VLDB Endowment 5 (10), 1040-1051, 2012 | 369 | 2012 |
| Efficient processing of k nearest neighbor joins using mapreduce W Lu, Y Shen, S Chen, BC Ooi arXiv preprint arXiv:1207.0141, 2012 | 360 | 2012 |
| Predicting multi-step citywide passenger demands using attention-based neural networks X Zhou, Y Shen, Y Zhu, L Huang Proceedings of the Eleventh ACM international conference on web search and …, 2018 | 166 | 2018 |
| A neural attention model for urban air quality inference: Learning the weights of monitoring stations W Cheng, Y Shen, Y Zhu, L Huang Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 163 | 2018 |
| Adaptive factorization network: Learning adaptive-order feature interactions W Cheng, Y Shen, L Huang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3609-3616, 2020 | 152 | 2020 |
| Stock price prediction using attention-based multi-input LSTM H Li, Y Shen, Y Zhu Asian conference on machine learning, 454-469, 2018 | 151 | 2018 |
| Next point-of-interest recommendation with temporal and multi-level context attention R Li, Y Shen, Y Zhu 2018 IEEE International Conference on Data Mining (ICDM), 1110-1115, 2018 | 131 | 2018 |
| Discovering queries based on example tuples Y Shen, K Chakrabarti, S Chaudhuri, B Ding, L Novik Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014 | 129 | 2014 |
| Dexter: large-scale discovery and extraction of product specifications on the web D Qiu, L Barbosa, XL Dong, Y Shen, D Srivastava Proceedings of the VLDB Endowment 8 (13), 2194-2205, 2015 | 82 | 2015 |
| DELF: A dual-embedding based deep latent factor model for recommendation. W Cheng, Y Shen, Y Zhu, L Huang IJCAI 18, 3329-3335, 2018 | 71 | 2018 |
| Inferring dockless shared bike distribution in new cities Z Liu, Y Shen, Y Zhu Proceedings of the eleventh ACM international conference on web search and …, 2018 | 59 | 2018 |
| Incorporating interpretability into latent factor models via fast influence analysis W Cheng, Y Shen, L Huang, Y Zhu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 56 | 2019 |
| Resolving training biases via influence-based data relabeling S Kong, Y Shen, L Huang International Conference on Learning Representations, 2021 | 54 | 2021 |
| Fast failure recovery in distributed graph processing systems Y Shen, G Chen, HV Jagadish, W Lu, BC Ooi, BM Tudor Proceedings of the VLDB Endowment 8 (4), 437-448, 2014 | 54 | 2014 |
| Sancus: staleness-aware communication-avoiding full-graph decentralized training in large-scale graph neural networks J Peng, Z Chen, Y Shao, Y Shen, L Chen, J Cao Proceedings of the VLDB Endowment 15 (9), 1937-1950, 2022 | 53 | 2022 |
| Forecasting wavelet transformed time series with attentive neural networks Y Zhao, Y Shen, Y Zhu, J Yao 2018 IEEE international conference on data mining (ICDM), 1452-1457, 2018 | 52 | 2018 |
| FluxEV: a fast and effective unsupervised framework for time-series anomaly detection J Li, S Di, Y Shen, L Chen Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 41 | 2021 |
| SMOPAT: Mining semantic mobility patterns from trajectories of private vehicles C Wan, Y Zhu, J Yu, Y Shen Information Sciences 429, 12-25, 2018 | 41 | 2018 |
| Differentiable neural input search for recommender systems W Cheng, Y Shen, L Huang arXiv preprint arXiv:2006.04466, 2020 | 39 | 2020 |
| LECF: recommendation via learnable edge collaborative filtering S Xiao, Y Shao, Y Li, H Yin, Y Shen, B Cui Science China Information Sciences 65 (1), 112101, 2022 | 38 | 2022 |
