Zhang Kai

Contact Information

Zhang Kai, Ph. D. graduate
Department of computer Science and Engineering
Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong

I am currently with the Life Science Division

Lawrence Berkeley National Lab.

You can reach me via kai_zhang@lbl.gov  


Bibliography  [CV]

I am a PhD graduate from the department of computer science and engineering, the Hong Kong University of Science and Technology. I got my master's degree from the National Laboratory of Pattern Recognition, Chinese Academy of Sciences in July, 2004. My advisor is Prof. James T. Kwok.

My PhD thesis Kernel based Clustering and Low Rank Approximation [pdf].

Research Interest [Research Statement]

Machine Learning: Large Scale Clustering, Manifold Learning, Semi-supervised Learning, Kernel Methods, Matrix Decomposition, Nonparametric Density Estimation

Applications: Data Mining, Complex Network, Document Processing, Bioinformatics, Topic Analysis, Speech Recognition

Teaching Assistant

Research Papers

Kai Zhang, James T. Kwok, Bahram Parvin. Prototype Vector Machine for Large Scale Semi-supervised Learning. In the 26th International Conference on Machine Learning (ICML 2009), Montreal, Canada, June 2009. [pdf] [slides]

Kai Zhang, Ivor W. Tsang, James T. Kwok. Improved Nystrom Low Rank Approximation and Error Analysis. In the 25th International Conference on Machine Learning (ICML 2008), Helsinki, Finland, June 2008 [pdf] [slides]

Project page: applying Improved Nystrom low-rank approximation for scalable manifold learning.  (codes updated, some bugs removed now)  

Kai Zhang, Ivor W. Tsang, James T. Kwok. Maximum Margin Clustering Made Practical. In the 24th International Conference on Machine Learning (ICML 2007), Oregen, USA, June 2007. [pdf] [poster] [matlab codes (updated)]

Kai Zhang, James T. Kwok. Simplifying Mixture Models Through Function Approximation. In the Neural Information Processing Systems (NIPS2006), Vancouver, Canada, December 2006. [pdf] [poster]

Kai Zhang, James T. Kwok. Block-Quantized  Kernel Matrix for Fast Spectral Embedding. In the 23rd International Conference on Machine Learning (ICML 2006), Pittsburgh, PA, USA, June 2006. [pdf] [slides]

Kai Zhang, James T. Kwok, M. Tang. Accelerated Convergence Using Dynamic Mean Shift. In the 9th European Conference on Computer Vision (ECCV 2006), Graz, Austria, May 2006. [pdf] [poster] [codes]

Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey J. Pan. Fast Speaker Adaptation via Maximum Penalized Likelihood Kernel Regression. In the International Conference on Acoustics, Speech, and Signal Processing (ICASSP'06), Toulouse, France, May 2006. [pdf]

Kai Zhang, M. Tang, J.T. Kwok. Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation. In the International Conference on Computer Vision and Pattern Recognition (CVPR 2005), San  Diego, CA, USA, June 2005. [pdf]

Intern Experience

June ~ September, 2007, Google Inc., Mountain View, CA (Supervisor: Phil Long).


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                                                               Last modified by Kai Zhang at 2/11/2008. All Rights Reserved.