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Home > People > Tie-Yan Liu
Tie-Yan Liu

Overview

    Tie-Yan Liu is a lead researcher at Microsoft Research Asia. He leads a team working on learning to rank for information retrieval, and large-scale graph learning. So far, he has more than 70 quality papers published in referred conferences and journals and over 50 filed US / international patents or pending applications. He is the co-author of the Best Student Paper for SIGIR 2008, and the Most Cited Paper for the Journal of Visual Communication and Image Representation (2004~2006). He is a Program Committee Co-Chair of RIAO 2010, an Area Chair of SIGIR 2008, SIGIR 2009, and AIRS 2009, a Co-Chair of SIGIR workshop on learning to rank for IR (LR4IR) 2007, 2008, and 2009, and a Program Committee member of many other international conferences such as WWW, ICML, ACL, and ICIP. He is on the Editorial Board of the Information Retrieval Journal (IRJ), and is a guest editor of the special issue on learning to rank of IRJ. He has given tutorials on learning to rank at several conferences including WWW 2009, WWW 2008, and SIGIR 2008. Prior to joining Microsoft, he obtained his Ph.D. in electronic engineering from Tsinghua University.

News

  • Data Release: Two datasets with thousands of queries added to LETOR 4.0, the benchmark dataset for learning to rank.
  • Book published: Learning to Rank for Information Retrieval, Now Publisher, 2009 (get an eletronic copy).
  • PC Co-Chair of RIAO 2010: Invited to serve as an PC Co-Chair for RIAO 2010, which will take place in Paris, France, April 2010.
  • Hiring: We are seeking candidates for research software development engineer (RSDE) and assistant researcher to work on the large-scale graph learning project. If you have interest, please send your resume to tyliu@microsoft.com.

Representative Publications

Learning to Rank

  1. Tie-Yan Liu. Learning to Rank for Information Retrieval, Foundation and Trends on Information Retrieval, Now Publishers, 2009.
  2. Jiang Bian, Tie-Yan Liu, Tao Qin, and Hongyuan Zha, Query-dependent Loss Function for Web Search. WSDM 2010.
  3. Fen Xia, Tie-Yan Liu, Hang Li, Statistical Consistency of Top-k Ranking, NIPS 2009.
  4. Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li, Ranking Measures and Loss Functions in Learning to Rank, NIPS 2009.
  5. Tao Qin, Tie-Yan Liu, Xudong Zhang, and Hang Li. Global Ranking Using Continuous Conditional Random Fields, NIPS 2008.
  6. Yanyan Lan, Tie-Yan Liu, Zhiming Ma, and Hang Li. Generalization Analysis of Listwise Learning to Rank Algorithms, ICML 2009.
  7. Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, and Hang Li. Listwise Approach to Learning to Rank: Theorem and Algorithm, ICML 2008.
  8. Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, and Hang Li. Query-level Stability and Generalization in Learning to Rank, ICML 2008.
  9. Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li. Learning to Rank: From Pairwise Approach to Listwise Approach. ICML 2007.
  10. Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, Hang Li, and Heung-Yeung Shum. Query-dependent Ranking using K-Nearest Neighbor, SIGIR 2008.
  11. Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, and Wei-Ying Ma. Directly Optimizing IR Evaluation Measures in Learning to Rank, SIGIR 2008.
  12. Tao Qin, Tie-Yan Liu, Jun Xu, and Hang Li. Making LETOR More Useful and Reliable, LR4IR 2008, in conjunction with SIGIR 2008.
  13. Xiubo Geng, Tie-Yan Liu, Tao Qin, and Hang Li. Feature Selection for Ranking, SIGIR 2007.
  14. Mingfeng Tsai, Tie-Yan Liu, Tao Qin, Hsin-Hsi Chen, and Wei-Ying Ma. FRank: A Ranking Method with Fidelity Loss, SIGIR 2007.
  15. Tao Qin, Tie-Yan Liu, Wei Lai, Xu-Dong Zhang, De-Sheng Wang, and Hang Li. Ranking with Multiple Hyperplanes, SIGIR 2007.
  16. Tie-Yan Liu, Jun Xu, Tao Qin, Wenying Xiong, and Hang Li. LETOR: Benchmark dataset for research on learning to rank for information retrieval, LR4IR 2007, in conjunction with SIGIR 2007.
  17. Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang and Hsiao-Wuen Hon. Adapting Ranking SVM to Document Retrieval, SIGIR 2006.
  18. Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Wen-Ying Xiong, and Hang Li. Learning to Rank Relational Objects and Its Application to Web Search, WWW 2008.
  19. Yuting Liu, Tie-Yan Liu, Tao Qin, Zhi-Ming Ma, and Hang Li. Supervised Rank Aggregation, WWW 2007.
  20. Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng Wang, Tie-Yan Liu, and Hang Li. Query-level Loss Function for Information Retrieval. Information Processing and Management, 2007.

Web Search

  1. Yuting Liu, Tie-Yan Liu, Zhiming Ma, and Hang Li. A Framework to Compute Page Importance based on User Behaviors, Information Retrieval Journal, 2009.
  2. Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, and Hang Li. BrowseRank: Letting Web Users Vote for Page Importance, SIGIR 2008. [SIGIR Best Student Paper Award]
  3. Guang Feng, Tie-Yan Liu, Ying Wang, Ting Bao, Zhiming Ma, Xu-Dong Zhang, and Wei-Ying Ma. AggregateRank: Bringing Order to Websites, SIGIR 2006.
  4. Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Zheng Chen, and Wei-Ying Ma. A Study on Relevance Propagation for Web Search, SIGIR 2005.
  5. Qiankun Zhao, Chuhong Hoi, Tie-Yan Liu, Sourav Bhowmick, Michael Lyu, and Wei-Ying Ma. Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data, WWW 2006.
  6. Qiankun Zhao, Tie-Yan Liu, Sourav Bhowmick, and Wei-Ying Ma. Event Detection from Evolution of Click-through Data, KDD 2006.
  7. Bin Gao, Tie-Yan Liu, Xin Zheng, Qian-Sheng Cheng, and Wei-Ying Ma. Consistent Bipartite Graph Co-Partitioning for Star-Structured High-Order Heterogeneous Data Co-Clustering, KDD 2005.
  8. Ying Bao, Guang Feng*, Tie-Yan Liu, Zhiming Ma, and Ying Wang. Ranking Websites: A Probabilistic View, Internet Mathematics, 2007.
  9. Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Guang Geng, De-Sheng Wang, and Wei-Ying Ma. Topic Distillation Via Subsite Retrieval, Information Processing and Management, 2006.
  10. Bin Gao, Tie-Yan Liu, Guang Feng, Tao Qin, Qian-Sheng Cheng, and Wei-Ying Ma. Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Co-partitioning, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2005.
  11. Tie-Yan Liu, Yiming Yang, Hao Wan, Hua-Jun Zeng, Zheng Chen, and Wei-Ying Ma. Support Vector Machines Classification with Very Large Scale Taxonomy, SIGKDD Explorations, 2005.

Multimedia

  1. Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, and Hong-Jiang Zhang. An Active Feedback Framework for Image Retrieval, Pattern Recognition Letters, 2007.
  2. Bin Gao, Tie-Yan Liu, Qian-Sheng Cheng, and Wei-Ying Ma. Web Image Clustering by Consistent Utilization of Visual Features and Surrounding Texts, ACM Multimedia 2005.
  3. Tie-Yan Liu, Kwok-Tung Lo, Xu-Dong Zhang, and Jian Feng. A New Cut Detection Algorithm with Constant False-Alarm Ratio for Video Segmentation, Journal of Visual Communications and Image Representation, 2004. [Most Cited Paper Award]
  4. Tie-Yan Liu, Xu-Dong Zhang, Jian Feng, and Kwok-Tung Lo. Shot Reconstruction Degree: a Novel Criterion for Key Frame Selection, Pattern Recognition Letters, 2004.
  5. Tie-Yan Liu, Kwok-Tung Lo, Jian Feng, and Xu-Dong Zhang. Frame Interpolation Scheme Using Inertia Motion Prediction. Signal Processing: Image Communication, 2003.
  6. Tie-Yan Liu, Jian Feng, Xu-Dong Zhang, and Kwok-Tung Lo. Inertia-based Cut Detection and Its Integration with Video Coder. IEE Proceedings on Vision, Image and Signal Processing, 2003.

Recent Professional Activities

[Last update: 2009-6-25]

Email: tyliu@microsoft.com
Mailing address: 4/F, Sigma Center, No.49, Zhichun Road, Haidian District, Beijing, 100190, P. R. China.

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