Yichuan Zhang

4th year PhD student in statistical machine learning at ANC,
School of Informatics,
University of Edinburgh.
Email: Y.Zhang-60@sms.ed.ac.uk
Supervisor: Charles Sutton

Research Interests

Machine learning allows us to handle data in a faster and more automate style. In real world, the data are usually corrupted, noisy, incomplete and changing over time. There is usually no unique understanding of the data. Bayesian statistics is one of the corner stones of machine learning to help us with all of these challenges. However, Bayesian inference itself is a great computational challenge. My work is focused on making Bayesian inference faster and more scalable. I'm also interested in the many applications using Bayesian inference, like active learning, transfer learning, and online Bayesian learning.

Publications

Quasi-Newton Markov chain Monte Carlo. Yichuan Zhang, Charles Sutton. In Advances in Neural Information Processing Systems (NIPS). 2011. last update at 23/4/2012
Continuous Relaxations for Discrete Hamiltonian Monte Carlo. Yichuan Zhang, Charles Sutton, Amos Storkey, Zoubin Zoubin Ghahramani. In Advances in Neural Information Processing Systems (NIPS). 2012. (Spotlight 72/1467 = 4.9%) last update at 14/11/2012

Code

BFGS Hamiltonian Monte Carlo last update at 19/4/2012

Some Useful Stuff

Matlab Usage
Radford Neal's blog





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