Conferences

Note: Asterisk * indicates publications on tenure track. Circle o indicates PI’s students or interns. Dagger   indicates publications as a mentor of PI’s students or interns. PI’s name is bold

Lingma Lu Acheson and Xia Ning*. Enhance online learning through data mining for personalized intervention. In 10th International Conference on Computer Supported Education, CSEDU’18, 2018, accepted.

Zhiyun Ren, Xia Ning*, and Huzefa Rangwala. ALE: Additive latent effect models for grade prediction. SDM’18, 2018. SIAM International Conference on Data Mining, accepted.

Wen-Hao Chiango, Li Shen, Lang Li, and Xia Ning*. Drug-drug interaction prediction based on co-medication patterns and graph matching. In International Conference on Intelligent Biology and Medicine, ICIBM’18.

Xia Ning*, Titus Schleyer, Li Shen, and Lang Li. Pattern discovery from directional high-order drug-drug interaction relations. In 2017 IEEE International Conference on Healthcare Informatics, ICHI’17, pages 154–162, Aug 2017. [ DOI ]

Xia Ning*, Li Shen, and Lang Li. Predicting high-order directional drug-drug interaction relations. In 2017 IEEE International Conference on Healthcare Informatics, ICHI’17, pages 556–561, Aug 2017. [ DOI ]

Junfeng Liuo and Xia Ning*. Differential compound prioritization via bi-directional selectivity push with power. In Proceedings of the 8th ACM Conference on Boinformatics, Computational Biology, and Health Informatics, BCB’17, pages 394–399, New York, NY, USA, 2017. ACM. [ DOI | http ]

Zhiyun Ren, Xia Ning*, and Huzefa Rangwala. Grade prediction with temporal course-wise influence. In Proceedings of the 10th International Confernece on Educational Data Mining, EDM’17, pages 48–56, 2017.

Xiao Biano, Feng Li, and Xia Ning*. Kernelized sparse self-representation for clustering and recommendation. In Proceedings of the 2016 SIAM International Conference on Data Mining, SDM’16, pages 10–17, 2016. [ DOI ]

Hongteng Xuo, Xia Ning*, Hui Zhang, Junghwan Rhee, and Guofei Jiang. Pinfer: Learning to infer concurrent request paths from system kernel events. In Proceedings of the 2016 IEEE International Conference on Autonomic Computing, ICAC’16, pages 199–208, 2016. [ DOI ]

Xiao Biano, Xia Ning*, and Geoff Jiang. Hierarchical sparse dictionary learning. In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, ECML/PKDD’15, pages 687–700, 2015. [ DOI ]

Jiaji Huango and Xia Ning*. Latent space tracking from heterogeneous data with an application for anomaly detection. In Proceedings of 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, Part I, PAKDD’15, pages 429–441, 2015. [ DOI ]

Tzu-Chun Lino and Xia Ning*. Multi-perspective modeling for click event prediction. In Proceedings of the 2015 International ACM Recommender Systems Challenge, RecSys’15, pages 11:1–11:4, 2015. [ DOI | http ]

Dixin Luo, Hongteng Xu, Yi Zhen, Xia Ning*, Hongyuan Zha, Xiaokang Yang, and Wenjun Zhang. Multi-task multi-dimensional hawkes processes for modeling event sequences. In Proceedings of the 24th International Joint Conference on Artificial Intelligence, IJCAI’15, pages 3685–3691, 2015. [ http ]

Jun Wang, Zhiyun Qian, Zhichun Li, Zhenyu Wu, Junghwan Rhee, Xia Ning*, Peng Liu, and Guofei Jiang. Discover and tame long-running idling processes in enterprise systems. In Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security, ASIA CCS’15, pages 543–554, 2015. [ DOI | http ]

Martin Renqiang Min, Xia Ning, Chao Cheng, and Mark Gerstein. Interpretable sparse high-order boltzmann machines. In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, AISTATS’14, pages 614–622, 2014. [ http ]

Santosh Kabbur, Xia Ning, and George Karypis. FISM: factored item similarity models for top-n recommender systems. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD’13, pages 659–667, 2013. [ DOI | http ]

Xia Ning and George Karypis. Sparse linear methods with side information for top-n recommendations. In Proceedings of 6th ACM Conference on Recommender Systems, RecSys’12, pages 155–162, 2012. [ DOI | http ]

Xia Ning and George Karypis. SLIM: Sparse linear methods for top-n recommender systems. In Proceedings of the 2011 IEEE 11th International Conference on Data Mining, ICDM’11, pages 497–506, Dec 2011. [ DOI ]

Xia Ning and Yanjun Qi. Semi-supervised convolution graph kernels for relation extraction. In Proceedings of the 11th SIAM International Conference on Data Mining, SDM’11, pages 510–521, 2011. [ DOI ]

Xia Ning, Michael A. Walters, and George Karypis. Improved machine learning models for predicting selective compounds. In Proceedings of the 2nd ACM International Conference on Bioinformatics, Computational Biology and Biomedicine, BCB’11, pages 106–115, 2011. [ DOI | http ]

Xia Ning and George Karypis. Multi-task learning for recommender system. In Proceedings of the 2nd Asian Conference on Machine Learning, ACML’10, pages 269–284, 2010. [ http ]

Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, and Xia Ning. Semi-supervised abstraction-augmented string kernel for multi-level bio-relation extraction. In Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, ECML/PKDD’10, pages 128–144, 2010. [ DOI ]

Xia Ning and George Karypis. The set classification problem and solution methods. In Proceedings of the SIAM International Conference on Data Mining, SDM’09, pages 847–858, 2009. [ DOI ]

Jianjun Chen, Yao Zheng, and Xia Ning. Scalable parallel quadrilateral mesh generation coupled with mesh partitioning. In Proceedings of the 6th International Conference on Parallel and Distributed Computing, PDCAT’05, pages 966–970, 2005. [ DOI ]