| Practical lessons from predicting clicks on ads at facebook X He, J Pan, O Jin, T Xu, B Liu, T Xu, Y Shi, A Atallah, R Herbrich, ... Proceedings of the eighth international workshop on data mining for online …, 2014 | 1096 | 2014 |
| Influence blocking maximization in social networks under the competitive linear threshold model X He, G Song, W Chen, Q Jiang Proceedings of the 2012 siam international conference on data mining, 463-474, 2012 | 539 | 2012 |
| Dyngem: Deep embedding method for dynamic graphs P Goyal, N Kamra, X He, Y Liu arXiv preprint arXiv:1805.11273, 2018 | 471 | 2018 |
| Robust Influencer Maximization X He, D Kempe Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge …, 2016 | 241 | 2016 |
| Glad: group anomaly detection in social media analysis R Yu, X He, Y Liu ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (2), 1-22, 2015 | 188 | 2015 |
| Hawkestopic: A joint model for network inference and topic modeling from text-based cascades X He, T Rekatsinas, J Foulds, L Getoor, Y Liu International conference on machine learning, 871-880, 2015 | 125 | 2015 |
| Influential node tracking on dynamic social network: An interchange greedy approach G Song, Y Li, X Chen, X He, J Tang IEEE Transactions on Knowledge and Data Engineering 29 (2), 359-372, 2016 | 91 | 2016 |
| Stability of influence maximization X He, D Kempe Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 84 | 2014 |
| mvn2vec: Preservation and collaboration in multi-view network embedding Y Shi, F Han, X He, X He, C Yang, J Luo, J Han arXiv preprint arXiv:1801.06597, 2018 | 67 | 2018 |
| On influential nodes tracking in dynamic social networks X Chen, G Song, X He, K Xie Proceedings of the 2015 SIAM International Conference on Data Mining, 613-621, 2015 | 51 | 2015 |
| Learning influence functions from incomplete observations X He, K Xu, D Kempe, Y Liu Advances in Neural Information Processing Systems 29, 2016 | 47 | 2016 |
| DECADE: a deep metric learning model for multivariate time series Z Che, X He, K Xu, Y Liu KDD workshop on mining and learning from time series, 2017 | 40 | 2017 |
| Stability and robustness in influence maximization X He, D Kempe ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (6), 1-34, 2018 | 37 | 2018 |
| Price of Anarchy for the N-Player Competitive Cascade Game with Submodular Activation Functions X He, D Kempe Web and Internet Economics: 9th International Conference, WINE 2013 …, 2013 | 32 | 2013 |
| Not enough data? joint inferring multiple diffusion networks via network generation priors X He, Y Liu Proceedings of the Tenth ACM International Conference on Web Search and Data …, 2017 | 21 | 2017 |
| Model selection for topic models via spectral decomposition D Cheng, X He, Y Liu Artificial Intelligence and Statistics, 183-191, 2015 | 18 | 2015 |
| Network inference from a mixture of diffusion models for fake news mitigation K Sharma, X He, S Seo, Y Liu Proceedings of the International AAAI Conference on Web and Social Media 15 …, 2021 | 17 | 2021 |
| Friend story ranking with edge-contextual local graph convolutions X Tang, Y Liu, X He, S Wang, N Shah Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 12 | 2022 |
| Query matching to media collections in a messaging system X He, J Luo, S Nayak, Z Ren, CJH Van Gysel US Patent 10,664,512, 2020 | 10 | 2020 |
| Query matching to media collections in a messaging system X He, J Luo, S Nayak, Z Ren, CJH Van Gysel US Patent 11,328,008, 2022 | 9 | 2022 |
Yan LiuProfessor, Director of Machine Learning Center@USCEmail verificata su usc.edu
