Liu, Li-Ping's Research Page

Brief CV

I received my B.S. in computer science from Hebei University of Technology in 2006. Then after three years' study in LAMDA group, I received my M.S. from Nanjing Univeristy in 2009. My advisor was Prof. Jiang, Yuan. Then I worked in Aliyun for one year and a half. After that, I began to pursue my PhD in Oregon State University. My advisor is Prof. Dietterich.

Research Interests

My research is mainly focused on graphical model, e.g. collective graphical model, inference and learning. I am also interested in superset label learning problem and learning theory.


Liu, L.-P., Dietterich, T.G., Li, N. and Zhou, Z.-H.. Transductive Optimization of Top k Precision. arXiv:1510.05976 [cs.LG]. 2015.

Liu, L.-P., Quanz, B., Xing, D., Deshpande, A. and Liu, X.. Predicting Weeks-Of-Supply via Sequence Aggregating. In: Proceedings of the 2015 INFORMS Workshop on Data Mining and Analytics. 2015.

Pei, Y, Liu, L.-P. and Fern, X.. Bayesian Active Clustering with Pairwise Constraints. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'2015).

Liu, L.-P., Sheldon, D. and Dietterich, T.. Gaussian Approximation of Collective Graphical Models. In: The 31st International Conference on Machine Learning (ICML’2014). [code]

Liu, L.-P. and Dietterich, T.. Learnability of the Superset Label Learning Problem. In: The 31st International Conference on Machine Learning (ICML’2014).

Liu, L.-P. and Dietterich, T.. A Conditional Multinomial Mixture Model for Superset Label Learning. In: 2012 Conference on Neural Information Processing Systems (NIPS’2012). [supp. marterial][code]

Liu, L.-P. and Fern Z. X.. Constructing Training Set for Outlier Detection. In: Proceedings of the 12th SIAM International Conference on Data Mining (SDM’12). pp. 919-929.

Hutchinson, R., Liu, L.-P. and Dietterich, T.. Incorporating Boosted Regression Trees into Ecological Latent Variable Models. In: Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI’2011). pp. 1343-1348.

Liu, L.-P., Jiang, Y. and Zhou, Z.-H.. Least Square Incremental Linear Discriminant Analysis. In: Proceedings of the 9th IEEE International Conference on Data Mining (ICDM’09). pp.298-306

Liu, L.-P., Yu, Y., Jiang, Y., and Zhou, Z.-H.. TEFE: A Time-Efficient Approach to Feature Extraction. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM’08). pp. 423-432.

Jiang, Y., Liu, L.-P.. Survey of Data Mining on Data Stream. Journal of Jiangnan University(Natural Science Edition). pp. 654-657.



In my research, some results are repeatedly used. I tidy up some of my notes and post it here. Hopefully it could benefit some others. 

  1. Linear Transformation of Multivariate Normal Distribution: Marginal, Joint and Posterior [pdf]

Link to my website

last updated on Nov. 12, 2015