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Xinhua Zhang (Henry)

NICTA-endorsed PhD Student
School of Computer Science, Australian National University

I am currently a visiting scholar at Purdue University.

 

Postal Address:

Department of Statistics

Purdue University

HAAS 174, 250 N University Street

West Lafayette, IN 47907-2066, USA

 

Tel: +1 (765) 496 9564 (O)
  +1 (765) 409 1439 (M)
Email:

 

Research Interests

My research interests are mainly nonparametric methods for machine learning.  This includes kernel methods and exponential families, especially support vector machines, conditional random fields, and nonparametric Bayesian methods. I am also interested in probabilistic modeling with graphical models and efficient inference.  Using undirected graphical models and kernel representation of distributions, I study the independence tests for structured data which has many applications to unsupervised learning.  In practice, large scale optimization techniques are required and I am particularly interested in first order methods such as cutting plane and bundle methods.

I work on applications in pattern recognition, document analysis, image processing, and any prediction problem that is useful in life.

Biography

I am a NICTA-endorsed PhD student of the School of Computer Science, Australian National University (ANU), since 31 March 2006. I am also affiliated with the Statistical Machine Learning Program of NICTA. From January 2004 to March 2006, I pursued my Master's degree (by research) at the Department of Computer Science, National University of Singapore (NUS). I received my B.E. Degree from the Department of Computer Science and Engineering at Shanghai Jiao Tong University in July 2003.

Selected Publications (Full list)

  1

 

Xinhua Zhang, Le Song, Arthur Gretton, Alex Smola

Kernel Measures of Independence for non-iid Data

Advances in Neural Information Processing Systems 21, 2008. [PDF]  [Appendix] [Spotlight]
  2

Le Song, Xinhua Zhang, Alex Smola, Arthur Gretton, and Bernhard Schölkopf

Tailoring Density Estimation via Reproducing Kernel Moment Matching

International Conference on Machine Learning, 2008.  [PDF]
  3

 

Li Cheng, S. V. N. Vishwanathan, and Xinhua Zhang

Consistent Image Analogies using Semi-supervised Learning

IEEE Conf. Computer Vision and Pattern Recognition, 2008.  [PDF]
  4

 

Xinhua Zhang, Douglas Aberdeen, and S. V. N. Vishwanathan

Conditional Random Fields for Multi-agent Reinforcement Learning

International Conference on Machine Learning, 2007.  [PDF] (Best student paper award)
  5

 

Xinhua Zhang and Wee Sun Lee

Hyperparameter Learning for Graph based Semi-supervised Learning Algorithms

Advances in Neural Information Processing Systems 19, 2006. [PDF]

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