Peer Referred Papers:

2011

• Jun Zhu, Ning Chen, and Eric P. Xing. Infinite Latent SVM for Classification and Multi-task Learning,
  To Appear in Advances in Neural Information Processing Systems (NIPS), Granada, Spain, 2011. (NIPS 2011)

• Jun Zhu, and Eric P. Xing. Sparse Topical Coding,
  To Appear in Proc. of 27th Conference on Uncertainty in Artificial Intelligence (UAI), Barcelona, Spain, 2011. (UAI 2011)

• Jun Zhu, Ni Lao, Ning Chen, and Eric P. Xing. Conditional Topical Coding: an Efficient Topic Model Conditioned on Rich Features,
  To Appear in Proc. of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, 2011. (SIGKDD 2011).

• Jun Zhu, Ning Chen, and Eric P. Xing. Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines,
  To Appear in Proc. of the 28th International Conference on Machine Learning, Bellevue, Washington, USA, 2011. (ICML 2011)

2010

• Jun Zhu, Li-Jia Li, Li Fei-Fei and Eric P. Xing. Large Margin Training of Upstream Scene Understanding Models,
  Advances in Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2010. (NIPS 2010)

• Seunghak Lee, Jun Zhu and Eric P. Xing. Detecting eQTLs using Adaptive Multi-task Lasso,
  Advances in Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2010. (NIPS 2010)

• Ning Chen, Jun Zhu and Eric P. Xing. Predictive Subspace Learning for Multiview Data: a Large Margin Approach,
  Advances in Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2010. (NIPS 2010)

• Ni Lao, Jun Zhu, Liu Liu, Yandong Liu and William Cohen. Efficient Relational Learning with Hidden Variable Detection,
  Advances in Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2010. (NIPS 2010)

• Jun Zhu and Eric P. Xing. Conditional Topic Random Fields,
  In Proc. of the 27th International Conference on Machine Learning, Haifa, Israel, 2010. (ICML 2010)

• Jun Zhu, Ni Lao, and Eric P. Xing. Grafting-Light: Fast, Incremental Feature Selection and Structure Learning of Markov Random Fields,
  In Proc. of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington DC, USA, 2010. (SIGKDD 2010)

2009

• Jun Zhu and Eric P. Xing. Maximum Entropy Discrimination Markov Networks,
  Journal of Machine Learning Research, 10(Nov):2531-2569, 2009. (JMLR 2009)

• Jun Zhu, and Eric P. Xing. On Primal and Dual Sparsity of Markov Networks,
  In Proc. of 26th International Conference on Machine Learning, Montreal, Canada, 2009. (ICML 2009)

• Jun Zhu, Amr Ahmed, and Eric P. Xing. MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification,
  In Proc. of 26th International Conference on Machine Learning, Montreal, Canada, 2009. (ICML 2009)

• Jun Zhu, Eric P. Xing, and Bo Zhang. Primal Sparse Max-Margin Markov Networks,
  In Proc. of 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, 2009. (SIGKDD 2009)

• Xiaolin Shi, Jun Zhu, Rui Cai, and Lei Zhang. User Grouping Behaviror in Online Forums,
  In Proc. of 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, 2009. (SIGKDD 2009)

• Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, and Ji-Rong Wen. StatSnowball: a Statistical Approach to Extracting Entity Relationships,
  In Proc. of 18th International Word Wide Web Conference, Madrid, Spain, 2009. (WWW 2009) (research full paper)

• Jiangming Yang, Rui Cai, Yida Wang, Jun Zhu, Lei Zhang, and Wei-Ying Ma. Incorporating Site-Level Knowledge to Extract Structured Data from Web Forums,
  In Proc. of 18th International Word Wide Web Conference, Madrid, Spain, 2009. (WWW 2009) (research full paper)

2008

• Jun Zhu , Zaiqing Nie, Bo Zhang, and Ji-Rong Wen. Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction,
  Journal of Machine Learning Research, 9(Jul):1583--1614, 2008. (JMLR 2008)

• Jun Zhu, Eric P. Xing, and Bo Zhang. Partially Observed Maximum Entropy Discrimination Markov Networks,
  Advances in Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2008. (NIPS 2008)

• Jun Zhu, Eric P. Xing, and Bo Zhang. Laplace Maximum Margin Markov Networks,
  In Proc. of the 25th International Conference on Machine Learning, Helsinki, Finland, 2008. (ICML 2008)

2007

• Jun Zhu, Zaiqing Nie, Bo Zhang, and Ji-Rong Wen. Dynamic Hierarchical Markov Random Fields and Their Application to Web Data Extraction,
  In Proc. of the 24th International Conference on Machine Learning, Corvalis, OR, USA, 2007. (ICML 2007)

• Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, and Hsiao-Wuen Hon. Webpage Understanding: an Integrated Approach,
  In Proc. of the 13rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, CA, USA, 2007. (SIGKDD 2007)

2006 & 2005

• Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, and Wei-Ying Ma. Simultaneous Record Detection and Attribute Labeling in Web Data Extraction,
  In Proc. of the 12nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, 2006. (SIGKDD 2006)

• Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, and Wei-Ying Ma. 2D Conditional Random Fields for Web Information Extraction,
  In Proc. of the 22nd International Conference on Machine Learning, Bonn, Germany, 2005. (ICML 2005)