Wei Liu 刘威 PhD Candidate in Digital Video and Multimedia Lab (DVMM) Supervisor: Professor Shih-Fu Chang Department of Electrical Engineering, Columbia University Email: wliu at ee.columbia.edu Research interests: machine learning, data mining, information retrieval, computer vision, and pattern recognition. My thesis is dedicated to large-scale machine learning algorithms for image classification and search. Resume Publications Courses Links

News

l I win Josef Raviv Memorial Postdoctoral Fellowship 2012-2013, and will join IBM T. J. Watson Research Center in September.

l One paper is accepted by Proceedings of the IEEE special issue.

l One paper is accepted by ICML’12. Thanks to Facebook Fellowship’s support.

l One paper is accepted by CVPR’12 oral session.

l I visited Facebook, Inc. at Palo Alto and gave a talk entitled “Large-Scale Classification and Nearest Neighbor Search”.

l Released the Matlab code for my CVPR’08 and TOMCCAP’10 papers.

l Released the Matlab code for my ICML’11 paper.

l I finished the wonderful summer intern with IBM T. J. Watson Research Center.

l I was awarded Facebook Fellowship 2011-2012 (one of five winners worldwide). Thanks to Facebook!

l One paper joint with IBM Research and Google Research was accepted by ICML’11.

l One paper joint with Kodak Research was accepted by CVPR’11.

l Released the Matlab code for my ICML’10 paper.

l Released the Matlab code for my CVPR’09 paper.

Significant Publications

1. Robust and Scalable Semi-Supervised Learning Wei Liu, Jun Wang, and Shih-Fu Chang. Proceedings of the IEEE 2012. New

2. Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval and Clustering Steven C. H. Hoi, Wei Liu, and Shih-Fu Chang. TOMCCAP 2010

(a long version of CVPR 2008 with code therein).

3. Compact Hyperplane Hashing with Bilinear Functions Wei Liu, Jun Wang, Yadong Mu, Sanjiv Kumar, and Shih-Fu Chang. ICML 2012 (oral). New

4. Hashing with Graphs Wei Liu, Jun Wang, Sanjiv Kumar, and Shih-Fu Chang. ICML 2011 (oral). code

5. Large Graph Construction for Scalable Semi-Supervised Learning Wei Liu, Junfeng He, and Shih-Fu Chang. ICML 2010 (oral). code

6. Semi-Supervised Sparse Metric Learning Using Alternating Linearization Optimization Wei Liu et al. KDD 2010 (full oral).

7. Supervised Hashing with Kernels Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, and Shih-Fu Chang. CVPR 2012 (oral). New

8. Noise Resistant Graph Ranking for Improved Web Image Search Wei Liu, Yu-Gang Jiang, Jiebo Luo, and Shih-Fu Chang. CVPR 2011.

9. Robust Multi-Class Transductive Learning with Graphs Wei Liu and Shih-Fu Chang. CVPR 2009. code

10. Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation Wei Liu et al. CVPR 2005 (oral).

11. Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval Steven C. H. Hoi, Wei Liu, and Shih-Fu Chang. CVPR 2008. code

12. A Face Annotation Framework with Partial Clustering and Interactive Labeling Yuandong Tian, Wei Liu, Rong Xiao, Fang Wen, and Xiaoou Tang. CVPR 2007.

13. Learning Distance Metrics with Contextual Constraints for Image Retrieval Steven C.H. Hoi, Wei Liu, Michael R. Lyu, and Wei-Ying Ma. CVPR 2006.

14. Nonparametric Subspace Analysis for Face Recognition Zhifeng Li, Wei Liu, Dahua Lin, and Xiaoou Tang. CVPR 2005.

15. Output Regularized Metric Learning with Side Information Wei Liu et al. ECCV 2008.

16. Spatio-temporal Embedding for Statistical Face Recognition from Video Wei Liu et al. ECCV 2006.

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