Department of Statistics, University of Illinois
   Department of Statistics                               UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
 
 

email: liangf*

phone: 217.333.6017

fax: 217.244.7190

 

office:

116A Illini Hall

725 S. Wright St.

Champaign, IL  61820

 

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 Feng Liang

Associate Professor of Statistics

Ph.D. in Statistics, Yale University, 2002

Website


Research Interests
  • Bayesian methods
  • Decision theory
  • Information theory
  • Minimum description length principle
  • Data mining

Selected Publications

  • B. Li, F. Liang, J. Hu, and X. He (2012) Reno: Regularized Nonparametric Analysis of Protein Lysate Array Data. Bioinformatics. In press.
  • E. I. George, F. Liang and X. Xu (2012) From Minimax Shrinkage Estimation to Minimax Shrinkage Prediction. Statistical Science 27: 82-94.
  • F. Liang (2012) Comment on Article by Sancetta. Bayesian Analysis 7:45-46.
  • Y. Yang, X. Chu, F. Liang, and T. Huang (2012) Pairwise Exemplar Clustering. In Proceedings of the 26th Conference on Artificial Intelligence, Toronto, Canada.
  • J. Xu and F. Liang (2010). Bayesian co-segmentation of multiple MR images. Statistics and Its Interface, 3 513-521.
  • X. Xu and F. Liang (2010). Asymptotic minimax risk of predictive density estimation for nonparametric regression. Bernoulli, 16(2) 543-560.
  • Gao J, Liang F, Fan W, Wang C, Sun Y, and Han J. (2010). On community outliers and their ecient detection in information networks. In Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Washington, DC.
  • J. Chu, M. Clyde, and F. Liang (2009). Bayesian function estimation using continuous wavelet dictionaries. Statistica Sinica, 19 1419-1438.
  • J. Gao, F. Liang, W. Fan, Y. Sun, and J. Han (2009). Bipartite Graph-based Consensus Maximization among Supervised and Unsupervised Models. In Proceedings of the 23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver, British Columbia, Canada.
  • F. Liang, R. Paulo, G. Molina, M. Clyde, and J. Berger (2008). Mixtures of g-priors for Bayesian variable selection. J. Amer. Statist. Assoc., 103 410-423.

© 2010 The Board of Trustees at the University of Illinois
Department of Statistics, University of Illinois at Urbana-Champaign
725 South Wright Street, Champaign, Illinois 61820 USA
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