| Dynamic stochastic blockmodels for time-evolving social networks KS Xu, AO Hero III IEEE Journal of Selected Topics in Signal Processing 8 (4), 552-562, 2014 | 272 | 2014 |
| Adaptive evolutionary clustering KS Xu, M Kliger, AO Hero III Data Mining and Knowledge Discovery 28 (2), 304-336, 2014 | 171 | 2014 |
| Consistent estimation of dynamic and multi-layer block models Q Han, KS Xu, EM Airoldi Proceedings of The 32nd International Conference on Machine Learning, 1511-1520, 2015 | 160 | 2015 |
| Stochastic block transition models for dynamic networks KS Xu Proceedings of the 18th International Conference on Artificial Intelligence …, 2015 | 120 | 2015 |
| Dynamic stochastic blockmodels: Statistical models for time-evolving networks KS Xu, AO Hero III Proceedings of the 6th International Conference on Social Computing …, 2013 | 111* | 2013 |
| DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks M Rahman, TK Saha, MA Hasan, KS Xu, CK Reddy arXiv preprint arXiv:1804.05755, 2018 | 51 | 2018 |
| A regularized graph layout framework for dynamic network visualization KS Xu, M Kliger, AO Hero III Data Mining and Knowledge Discovery 27 (1), 84-116, 2013 | 48 | 2013 |
| Evolutionary spectral clustering with adaptive forgetting factor KS Xu, M Kliger, AO Hero III Proceedings of the IEEE International Conference on Acoustics, Speech, and …, 2010 | 43 | 2010 |
| A compressed sensing based decomposition of electrodermal activity signals S Jain, U Oswal, KS Xu, B Eriksson, J Haupt IEEE Transactions on Biomedical Engineering 64 (9), 2142-2151, 2017 | 42 | 2017 |
| Tracking communities in dynamic social networks KS Xu, M Kliger, AO Hero III Proceedings of the 4th International Conference on Social Computing …, 2011 | 42 | 2011 |
| Revealing social networks of spammers through spectral clustering KS Xu, M Kliger, Y Chen, PJ Woolf, AO Hero III Proceedings of the IEEE International Conference on Communications, 2009 | 40 | 2009 |
| Unsupervised motion artifact detection in wrist-measured electrodermal activity data Y Zhang, M Haghdan, KS Xu Proceedings of the 21st ACM International Symposium on Wearable Computers, 54-57, 2017 | 39 | 2017 |
| Multi-criteria anomaly detection using Pareto depth analysis KJ Hsiao, KS Xu, J Calder, AO Hero III Advances in Neural Information Processing Systems 25, 854-862, 2012 | 39 | 2012 |
| The block point process model for continuous-time event-based dynamic networks R Junuthula, M Haghdan, KS Xu, V Devabhaktuni The World Wide Web Conference, 829-839, 2019 | 35 | 2019 |
| Regularized parametric regression for high-dimensional survival analysis Y Li, KS Xu, CK Reddy Proceedings of SIAM International Conference on Data Mining, 2016 | 35 | 2016 |
| Evaluating link prediction accuracy on dynamic networks with added and removed edges RR Junuthula, KS Xu, VK Devabhaktuni Proceedings of the 9th IEEE International Conference on Social Computing and …, 2016 | 32 | 2016 |
| Multicriteria similarity-based anomaly detection using Pareto depth analysis KJ Hsiao, KS Xu, J Calder, AO Hero IEEE Transactions on Neural Networks and Learning Systems 27 (6), 1307-1321, 2016 | 30 | 2016 |
| CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation M Arastuie, S Paul, K Xu Advances in Neural Information Processing Systems 33, 2020 | 24 | 2020 |
| Pilot Skill Level and Workload Prediction for Sliding-Scale Autonomy SKR Nittala, CP Elkin, JM Kiker, R Meyer, J Curro, AK Reiter, KS Xu, ... 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 15 | 2018 |
| Empirical Comparison of Continuous and Discrete-time Representations for Survival Prediction M Sloma, F Syed, M Nemati, KS Xu Survival Prediction-Algorithms, Challenges and Applications, 118-131, 2021 | 14 | 2021 |
Alfred HeroJohn H Holland Distinguished University Professor, University of Michigan在 eecs.umich.edu 的电子邮件经过验证
