| Mist: A multiview and multimodal spatial-temporal learning framework for citywide abnormal event forecasting C Huang, C Zhang, J Zhao, X Wu, D Yin, N Chawla The world wide web conference, 717-728, 2019 | 118 | 2019 |
| Automated relational meta-learning H Yao, X Wu, Z Tao, Y Li, B Ding, R Li, Z Li arXiv preprint arXiv:2001.00745, 2020 | 117 | 2020 |
| Neural tensor factorization for temporal interaction learning X Wu, B Shi, Y Dong, C Huang, NV Chawla Proceedings of the Twelfth ACM international conference on web search and …, 2019 | 105 | 2019 |
| Online purchase prediction via multi-scale modeling of behavior dynamics C Huang, X Wu, X Zhang, C Zhang, J Zhao, D Yin, NV Chawla Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 104 | 2019 |
| Hierarchically structured transformer networks for fine-grained spatial event forecasting X Wu, C Huang, C Zhang, NV Chawla Proceedings of the web conference 2020, 2320-2330, 2020 | 68 | 2020 |
| Restful: Resolution-aware forecasting of behavioral time series data X Wu, B Shi, Y Dong, C Huang, L Faust, NV Chawla Proceedings of the 27th ACM International Conference on Information and …, 2018 | 62 | 2018 |
| Crowdsourcing-based urban anomaly prediction system for smart cities C Huang, X Wu, D Wang Proceedings of the 25th ACM international on conference on information and …, 2016 | 47 | 2016 |
| Click feedback-aware query recommendation using adversarial examples R Li, L Li, X Wu, Y Zhou, W Wang The World Wide Web Conference, 2978-2984, 2019 | 43 | 2019 |
| Uapd: Predicting urban anomalies from spatial-temporal data X Wu, Y Dong, C Huang, J Xu, D Wang, NV Chawla Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 40 | 2017 |
| Jointly predicting job performance, personality, cognitive ability, affect, and well-being P Robles-Granda, S Lin, X Wu, GJ Martinez, SM Mattingly, E Moskal, ... IEEE Computational Intelligence Magazine 16 (2), 46-61, 2021 | 39 | 2021 |
| Few-shot learning for new user recommendation in location-based social networks R Li, X Wu, X Wu, W Wang Proceedings of The Web Conference 2020, 2472-2478, 2020 | 39 | 2020 |
| Reliable fake review detection via modeling temporal and behavioral patterns X Wu, Y Dong, J Tao, C Huang, NV Chawla 2017 IEEE International Conference on Big Data (Big Data), 494-499, 2017 | 37 | 2017 |
| Adversarial learning to compare: Self-attentive prospective customer recommendation in location based social networks R Li, X Wu, W Wang Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 36 | 2020 |
| Filling missing values on wearable-sensory time series data S Lin, X Wu, G Martinez, NV Chawla Proceedings of the 2020 SIAM International Conference on Data Mining, 46-54, 2020 | 36 | 2020 |
| Neural tensor factorization X Wu, B Shi, Y Dong, C Huang, N Chawla arXiv preprint arXiv:1802.04416, 2018 | 24 | 2018 |
| Who will attend this event together? Event attendance prediction via deep LSTM networks X Wu, Y Dong, B Shi, A Swami, NV Chawla Proceedings of the 2018 SIAM International Conference on Data Mining, 180-188, 2018 | 22 | 2018 |
| Self-paced robust learning for leveraging clean labels in noisy data X Zhang, X Wu, F Chen, L Zhao, CT Lu Proceedings of the AAAI conference on artificial intelligence 34 (04), 6853-6860, 2020 | 21 | 2020 |
| Deep prototypical networks for imbalanced time series classification under data scarcity C Huang, X Wu, X Zhang, S Lin, NV Chawla Proceedings of the 28th ACM international conference on information and …, 2019 | 19 | 2019 |
| Personalized imputation on wearable-sensory time series via knowledge transfer X Wu, S Mattingly, S Mirjafari, C Huang, NV Chawla Proceedings of the 29th ACM International Conference on Information …, 2020 | 17 | 2020 |
| Relation-aware meta-learning for e-commerce market segment demand prediction with limited records J Shi, H Yao, X Wu, T Li, Z Lin, T Wang, B Zhao Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 15 | 2021 |
