| Asynchronous online federated learning for edge devices with non-iid data Y Chen, Y Ning, M Slawski, H Rangwala 2020 IEEE International Conference on Big Data (Big Data), 15-24, 2020 | 223 | 2020 |
| Learning dynamic context graphs for predicting social events S Deng, H Rangwala, Y Ning Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 80 | 2019 |
| Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning Y Ning, S Muthiah, H Rangwala, N Ramakrishnan Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and …, 2016 | 65 | 2016 |
| Dynamic knowledge graph based multi-event forecasting S Deng, H Rangwala, Y Ning Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 53 | 2020 |
| Cola-GNN: Cross-location attention based graph neural networks for long-term ILI prediction S Deng, S Wang, H Rangwala, L Wang, Y Ning Proceedings of the 29th ACM international conference on information …, 2020 | 52 | 2020 |
| A multiple instance learning framework for identifying key sentences and detecting events W Wang, Y Ning, H Rangwala, N Ramakrishnan Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 38 | 2016 |
| Empirical analysis of multi-task learning for reducing identity bias in toxic comment detection A Vaidya, F Mai, Y Ning Proceedings of the International AAAI Conference on Web and Social Media 14 …, 2020 | 33 | 2020 |
| Graph message passing with cross-location attentions for long-term ILI prediction S Deng, S Wang, H Rangwala, L Wang, Y Ning arXiv preprint arXiv:1912.10202, 2019 | 22 | 2019 |
| STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting Y Ning, R Tao, CK Reddy, H Rangwala, JC Starz, N Ramakrishnan The 18th SIAM International Conference on Data Mining (SDM18), 2018 | 22 | 2018 |
| A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation Y Ning, Y Shi, L Hong, H Rangwala, N Ramakrishnan Proceedings of the 11th ACM Conference on Recommender Systems (RecSys’17), 2017 | 20 | 2017 |
| Generating Realistic Synthetic Population Datasets H Wu, Y Ning, P Chakraborty, J Vreeken, N Tatti, N Ramakrishnan ACM Transactions on Knowledge Discovery from Data (TKDD), 2018 | 19 | 2018 |
| Topical analysis of interactions between news and social media T Hua, Y Ning, F Chen, CT Lu, N Ramakrishnan Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 19 | 2016 |
| Empirical analysis of multi-task learning for reducing model bias in toxic comment detection A Vaidya, F Mai, Y Ning arXiv preprint arXiv:1909.09758, 2019 | 18 | 2019 |
| Collaborative graph learning with auxiliary text for temporal event prediction in healthcare C Lu, CK Reddy, P Chakraborty, S Kleinberg, Y Ning Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 17 | 2021 |
| Determining relative airport threats from news and social media R Khandpur, T Ji, Y Ning, L Zhao, CT Lu, E Smith, C Adams, ... Proceedings of the AAAI Conference on Artificial Intelligence 31 (2), 4701-4707, 2017 | 17 | 2017 |
| Fairness of classification using users’ social relationships in online peer-to-peer lending Y Li, Y Ning, R Liu, Y Wu, W Hui Wang Companion Proceedings of the Web Conference 2020, 733-742, 2020 | 16 | 2020 |
| Spatio-temporal event forecasting and precursor identification Y Ning, L Zhao, F Chen, CT Lu, H Rangwala Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 14 | 2019 |
| Algorithmic fairness in computational medicine J Xu, Y Xiao, WH Wang, Y Ning, EA Shenkman, J Bian, F Wang eBioMedicine, Part of THE LANCET Discovery Science 84, 2022 | 13 | 2022 |
| Uncovering news-twitter reciprocity via interaction patterns Y Ning, S Muthiah, R Tandon, N Ramakrishnan 2015 IEEE/ACM International Conference on Advances in Social Networks …, 2015 | 13 | 2015 |
| Using decision tree to predict mental health status based on web behavior T Zhu, Y Ning, A Li, X Xu 2011 3rd Symposium on Web Society, 27-31, 2011 | 12 | 2011 |
Huzefa RangwalaProfessor & Lawrence Cranberg Research Faculty Fellow在 cs.gmu.edu 的电子邮件经过验证
