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Henry (Xinhua)  ZHANG     

 

PhD Student NICTA-endorsed PhD Student
Computer Sciences Laboratory
RSISE
The Australian National University

Statistical Machine Learning Program

National ICT Australia

 

Lab:       Level 3, Tower A, 7 London Circuit, Canberra, ACT 2601, Australia

Home:   Rm 403, Garden Wing, UniHouse, ANU, Acton, ACT 2601, Australia   (history)

Postal Address:  Locked Bag 8001, SML NICTA, Canberra ACT 2601, Australia

Phone:    Lab phone:      +61 (2)  62676304
      
         Mobile phone:   +61 -402-556-837

FAX:       +61 (2) 6230 7499

MSN:              (Feel free to send me an email if you add me.)

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Email:      , , OR  

 


NEW:

 

Kernel Measures of Independence for non-iid Data  [long version]

              Xinhua Zhang,  Le SongArthur Gretton, Alex Smola, Accepted by NIPS 2008 for spotlight poster

A Very Gentle Note on the Construction of Dirichlet Process (technical note)

Tailoring Density Estimation via Reproducing Kernel Moment Matching

              Le Song, Xinhua Zhang,  Alex Smola, Arthur Gretton, Bernhard Schölkopf,   ICML 2008

Consistent Image Analogies using Semi-supervised Learning  

              Li Cheng, S.V.N. Vishwanathan, Xinhua Zhang,  CVPR 2008

Microsoft Fellow 2007

Short Bio: Mr. Zhang, Xinhua is a NICTA-endorsed PhD student of the Computer Sciences Laboratory, Research School of Information Sciences and Engineering, The Australian National University, since 31 March, 2006.  He is also with the Statistical Machine Learning Group of NICTA.  From January 2004 to March 2006, he pursued his Master's degree (by research) at the Department of Computer Science, School of Computing (SoC) National University of Singapore (NUS) , where he worked as a research assistant under the Computer Science program of Singapore-MIT Alliance (SMA) for the last 9 months.  He received his Bachelor’s Degree from the Department of Computer Science and Engineering at Shanghai Jiao Tong University in July, 2003. 

Research interest: machine learning, especially graphical models, kernel methods, semi-supervised learning, exponential families, Gaussian processes, Bregman divergence and differential geometry.

Supervisors: Dr. S.V.N. Vishwanathan, Dr. Alex Smola, Dr. Wray Buntine

Last update: 1 January, 2009

 

Quote

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It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way- in short, the period was so far like the present period, that some of its noisiest authorities insisted on its being received, for good or for evil, in the superlative degree of comparison only.

From Charles Dickens - Tale of Two Cities

 

 

 

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