Changyou Chen

I am currently a PhD candidate in College of Engineering and Computer Science, the Australian National University. I am also affiliated with the Statistical Machine Learning (SML) group at National ICT Australia (NICTA). My primary supervisor is Prof. Wray Buntine.

I received my bachelor and master degrees in 2007 and 2010,respectively, both from School of Computer Science, Fudan University, Shanghai, China, supervised by Prof. Junping Zhang.

You can find my curriculum vitae here.

I have broad research interest in machine learning, but now focus on Bayesian nonparametrics. Specifically, I am/was working on:

• Dependent Normalized Random Measures, Dependent Poisson-Kingman Processes
  
• Some topics on Diffusion Processes
  
• MCMC for Hierarchical Poisson-Dirichlet Processes
  
• Topic Models
  
• Manifold Learning, Gait Recognition (master research topics)
  

Dependent Normalized Random Measures
PhD thesis, the Australian National University, 2014.
Supervisor: Wray Buntine
[PDF]

Changyou Chen, Jun Zhu, Xinhua Zhang
Robust Bayesian Max-Margin Clustering
To Appear in Advances in Neural Information Processing Systems (NIPS), Montreal, Canada, 2014.
[PDF] [supplement] [poster]

Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert Skeel, Hartmut Neven
Bayesian Sampling Using Stochastic Gradient Thermostats
To Appear in Advances in Neural Information Processing Systems (NIPS), Montreal, Canada, 2014.
[PDF] [supplement] [poster]

Changyou Chen, Wray Buntine, Nan Ding, Lexing Xie, Lan Du
Differential Topic Models
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
[PrePrint] [supplement]

Kar Wai Lim, Changyou Chen, Wray Buntine
Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling
NIPS Workshop on Topics Model: Computation, Application, and Evaluation, Nevada, USA, 2013.
[PDF] [supplement] [poster]

Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh
Dependent Normalized Random Measures
International Conference on Machine Learning (ICML), Atlanta, USA, 2013.
[PDF] [supplement] [slides, Vinayak_slides] [poster]

Changyou Chen, Wray Buntine, Nan Ding
Theory of Dependent Hierarchical Normalized Random Measures
Technical Report arXiv:1205.4159, NICTA and ANU, 2012.
[PDF] [link]

Changyou Chen, Nan Ding, Wray Buntine
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling
International Conference on Machine Learning (ICML), Edinburgh, British, 2012.
[PDF] [slides] [poster]

Changyou Chen, Lan Du, Wray Buntine
Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process
European Conference on Machine Learning (ECML-PKDD), Athens, Greece, pp. 296-311, 2011.
[PDF] [slides] [poster] [errata]

Lan Du, Wray Buntine, Huidong Jin, Changyou Chen
Sequential Latent Dirichlet Allocation
Knowledge and Inforamtion Systems, vol. 31, no. 3, pp. 475-503, 2012.
[PDF] [link]

Changyou Chen, Junping Zhang, Xuefang He, Zhi-Hua Zhou
Efficient Non-Parametric Kernel Learning with Robust Pairwise Constraints
International Journal of Machine Learning and Cybernetics, vol. 3, pp. 83-96, 2011.
[link]

Junping Zhang, Jian Pu, Changyou Chen, Rudolf Fleischer
Low-resolution Gait Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 4, pp. 986-996, 2010

Changyou Chen, Junping Zhang, Rudolf Fleischer
Distance Approximating Dimension Reduction of Riemannian Manifolds
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 1, pp. 208-217, 2010

Changyou Chen, Junping Zhang, Rudolf Fleischer
Multiliear Tensor-based Nonparametric Dimension Reduction
The 3rd IAPR/IEEE International Conference on Biometrics (ICB 2009), LNCS5558, pp. 1037-1046, Springer-Verlag Berlin Heidelberg, 2009

Junping Zhang, Yuan Cheng, Changyou Chen
Low Resolution Gait Recognition with High Frequency Super Resolution
The Tenth Pacific Rim International Conference on Artificial Intelligence (PRICAI 08), LNAI 5351, pp. 533-543, Springer-Verlag Berlin Heidelberg, 2008