Publications

2009

  • Y.Liu, A. Niculescu-Mizil, W. Gryc. Topic-Link LDA: Joint Models of Topic and Author Community. International conference on Machine Learning  (ICML’09), 2009 [PDF].

 

  • Y. Liu, J.R. Kalagnanam, O. Johnsen. Learning Dynamic Temporal Graphs for Oil-production Equipment Monitoring System. International Conference on Knowledge Discovery and Data Mining (KDD' 09), 2009 [PDF].

 

  • A. Lozano, H. Li, A. Niculescu-Mizil, Y. Liu, C. Perlich, J. Hosking, N. Abe. Spatial-temporal causal modeling for climate change attribution. International Conference on Knowledge Discovery and Data Mining (KDD' 09), 2009 [PDF].

 

  • A.C. Lozano, N. Abe, Y. Liu, S. Rosset.  Grouped Graphical Granger Modeling Methods for Temporal Causal Modeling. International Conference on Knowledge Discovery and Data Mining (KDD' 09), 2009 [PDF].

 

  • A.C. Lozano, N. Abe, Y. Liu, S. Rosset. Grouped Graphical Granger Modeling for Gene Expression Regulatory Networks Discovery. International Conference on Intelligent Systems for Molecular Biology (ISMB’09), 2009 [PDF].

 

  • Y. Liu, P. Hsueh, J. Lai, M. Sangin, M.A. Nussli, P. Dillenbourg. Who is the Expert? Analyzing Gaze Data to Predict Expertise Level in Collaborative Applications. International Conference on Multimedia & Expo (ICME’09), 2009 [PDF].

 

  • T. Ide, A. Lozano, N. Abe, Y. Liu. Proximity-Based Anomaly Detection using Sparse Structure Learning. SIAM Conference on Data Mining (SDM’09), 2009 [PDF]. 

 

2008

·        J. He, Y. Liu, R. Lawrence. Graph-based Rare Category Detection. To appear in International Conference on Data Mining (ICDM-08), 2008 [PDF].

 

·        C. Perlich, P. Melville, Y. Liu, G. Swirszcz, R. Lawrence. Winner’s Report: KDD CUP Breast Cancer Identification. In Proceedings of the KDD-08 Workshop on Mining Medical, 2008 [PDF]. .  Winner of  KDD Cup 2008 on Early Breast Cancer Detection.

 

·        Y. Liu, Z. Kou, C. Perlich, R. Lawrence. Intelligent System for Workforce Classification.  In proceedings of In Proceedings of the KDD-08 Workshop on Data Mining for Business Applications, 2008 [PDF].

 

 

2007

·      A. Arnold, Y. Liu, N. Abe. Temporal Causal Modeling with Graphical Granger Methods. In proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD-07), 2007. [PDF]

 

·       S. Rosset, C. Perlich, Y. Liu. Making the Most of Your Data: KDD Cup 2007 "How Many Ratings" Winners Report. In proceedings of KDD Cup and Workshop 2007.  First place for KDD Cup 2007 of Netflix “How Many Ratings in 2006” task. [PDF]

 

·       Y. Liu, Z. Kou. Predicting Who Rated What in Large-Scale Datasets. In proceedings of KDD Cup and Workshop 2007.  Second Runner-up for KDD Cup 2007 of Netflix “Who Rated What in 2006” task. [PDF]

 

·       M. Helander, R. Lawrence, Y. Liu, C. Perlich, C. Reddy, S. Rosset. Looking for Great Ideas: Analyzing the Innovation Jam. In proceedings of KDD Workshop on Web Mining and Social Network Analysis, 2007.  [PDF]

 

·       P. Melville, Y. Liu, R. Lawrence, I. Khabibrakhmanov, C. Pendus, T. Bowden. Finding New Customers Using Unstructured and Structured Data. In proceedings of KDD Workshop on Web Mining Multiple Information Sources, 2007.  [PDF]

 

·        J. Yang, Y. Liu, E. P. Xing, A. Hauptmann. Harmonium Models for Semantic Video Representation and Classification.  In SIAM Conf. on Data Mining 2007, Minneapolis, Minnesota, Apr. 26-28, 2007. Winner of the Best Application Paper Award [PDF]

 

·        Y. Liu, J G. Carbonell, V. Gopalakrishnan, P. Weigele. Protein Quaternary Fold Recognition Using Conditional Graphical Models. International Joint Conference in Artificial Intelligence (IJCAI-07) [PDF]

 

·        J. He, J. Carbonell, Y. Liu. Graph-Based Semi-Supervised Learning as a Generative Model. International Joint Conference in Artificial Intelligence (IJCAI-07), 2007 [PDF]

 

·        K. Probst, R. Ghani, M. Krema, A. Fano, Y. Liu. Semi-supervised Learning of Attribute-Value Pairs from Product Descriptions.  International Joint Conference in Artificial Intelligence (IJCAI-07) [PDF]

 

 

2006

 

·        R. Ghani, K. Probst, Y. Liu, M. Krema, and A. Fano. Text Mining to Extract Product Attributes. SIGKDD Explorations (2006) [PDF]

 

·        Y. Liu, J. Carbonell, P. Weigele, V. Gopalakrishnan. Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs).  Journal of Computational Biology [PDF]

 

 

2005

                                                                                                                                                                              

·        Y. Liu, E. P. Xing, J. Carbonell. Predicting Protein Folds with Structural Repeats Using a Chain Graph Model. International conference on Machine Learning  (ICML’05), 2005 [PDF]

 

·        Y. Liu, J. Carbonell, P. Weigele, V. Gopalakrishnan. Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition. International conference on Research in Computational Molecular Biology (RECOMB’05), 2005 [PDF]

 

 2004

 

·        J. Lafferty, X. Zhu, Y. Liu. Kernel Conditional Random Fields: Representation and Clique Selection. International Conference on Machine Learning (ICML'04), 2004 [PDF]. An earlier version of the paper can be found in CMU technical report CMU-CS-04-115, 2004.

 

·        Y. Liu, J. Carbonell, J. Klein-Seetharaman, V. Gopalakrishnan. Comparison of Probabilistic Combination Methods for Protein Secondary Structure Prediction. Bioinformatics. 2004 Nov 22;20(17):3099-107 [PDF]

 

·        Y. Liu, J. Carbonell, J. Klein-Seetharaman, V. Gopalakrishnan. Context Sensitive Vocabulary and Its Application in Protein Secondary Structure Prediction.  International Conference on Research and Development in Information Retrieval (SIGIR'04), 2004. (Poster) [PDF]

 

 

2003 and earlier 

 

·        R. Jin, Y. Liu, S. Luo, J. Carbonell and A. Hauptmann.  A New Boosting Algorithm Using Input-Dependent Regularizer. International Conference on Machine Learning (ICML'03), 2003 [PDF]

 

·        Y. Liu, J. Carbonell and R. Jin. A New Pairwise Ensemble Approach for Text Classification.  European Conference on Machine Learning (ECML'03), 2003 [PDF]

 

·        R Yan, Y. Liu, R. Jin and A. Hauptmann. On Predicting Rare Class with SVM Ensemble in Scene Classification. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), Hong Kong, China, April 6-10, 2003 [PDF]

 

·        Y. Liu, Y, Yang and J. Carbonell. Boosting to Correct the Inductive Bias for Text Classification. ACM International Conference on Information and Knowledge Management (CIKM’02), Nov 4 - Nov 9, 2002 [pdf]