Liping Liu

Postdoctoral Researcher

Advised by David Blei
Data Science Institue
Columbia University
New York, New York, 10027

E-mail: ll3105 [@] columbia [.] edu

Liping Liu

Page Contents: Curriculum Vitae Research Publications Materials Bio Sketch


Research

My research mainly focuses on machine learning problems arising in real applications.

Current Research

Finished research projects (Some of them are still ongoing)

Publications

Liu, L.-P.. Machine Learning Methods for Computational Sustainability. PhD Thesis, Oregon State University, 2016. [pdf]

Liu, L.-P., Dietterich, T.G., Li, N., and Zhou, Z.-H.. Transductive Optimization of Top k Precision. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016).

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, X.. Constructing Training Set for Outlier Detection. In: Proceedings of the 12th SIAM International Conference on Data Mining (SDM'12).

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)

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).

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)

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

Materials and Links

Bio Sketch

I received my B.S. in computer science from Hebei University of Technology in 2006. After three years' study in LAMDA group, I received my M.S. from Nanjing Univeristy in 2009. My advisor was Prof. Yuan Jiang and Zhi-Hua Zhou. Then I worked in Alibaba for one year and a half. After that, I spent six years to finish my PhD at Oregon State University. My PhD advisor was Prof. Thomas Dietterich.

Last updated 09/11/2016, Liping Liu

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