Publications

11.
Ekaterina Merkurjev, Andrea Bertozzi, Xiaoran Yan, and Kristina Lerman. Modified Cheeger and Ratio Cut Methods Using the Ginzburg-Landau Functional for Classification of High-Dimensional Data. To appear as a Special Issue Article in Inverse Problems.
10.
Yan, X. Bayesian Model Selection for Stochastic Block Models. To appear in IEEE ASONAM 2016.
9.
Yan,X., Teng S., Lerman K., Ghosh R. Capturing the interplay of dynamics and  networks through parameterizations of Laplacian operators. https://peerj.com/articles/cs-57/
8.
Lerman, K., Yan, X. & Wu, X.-Z. The Majority Illusion in Social Networks. PLoS One (2016). http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147617
7.
Daianu, M. et al. Information-theoretic Characterization of Neuroimaging Derived Metrics for Cognitive Decline in the Elderly. (2015).
6.
Gupta, S., Yan, X. & Lerman, K. Structural Properties of Ego Networks. in Social Computing, Behavioral-Cultural Modeling, and Prediction (eds. Agarwal, N., Xu, K. & Osgood, N.) 9021, 55–64 (Springer International Publishing, 2015).
5.
Ghosh, R., Teng, S., Lerman, K. & Yan, X. The Interplay Between Dynamics and Networks: Centrality, Communities, and Cheeger Inequality. in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 1406–1415 (ACM, 2014). http://doi.acm.org/10.1145/2623330.2623738
4.
Zhu, Y., Yan, X. & Moore, C. Oriented and degree-generated block models: generating and inferring communities with inhomogeneous degree distributions. Journal of Complex Networks2, 1–18 (2014). http://comnet.oxfordjournals.org/content/2/1/1.abstract
3.
Yan, X. et al. Model selection for degree-corrected block models. Journal of Statistical Mechanics: Theory and Experiment2014, P05007 (2014). http://stacks.iop.org/1742-5468/2014/i=5/a=P05007
2.
Zhu, Y., Yan, X., Getoor, L. & Moore, C. Scalable Text and Link Analysis with Mixed-topic Link Models. in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 473–481 (ACM, 2013). http://doi.acm.org/10.1145/2487575.2487693
1.
Moore, C., Yan, X., Zhu, Y., Rouquier, J.-B. & Lane, T. Active Learning for Node Classification in Assortative and Disassortative Networks. in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 841–849 (ACM, 2011). http://doi.acm.org/10.1145/2020408.2020552