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Research | Publication | Education
My research area is machine learning, focusing on problems of learning, inference and decision making under the framework of graphical models.
Variational algorithms for marginal MAP;
Liu, Ihler; Uncertainty in Artificial Intelligence (UAI) 2011.
Bounding the Partition Function using Holder's Inequality;
Liu, Ihler; International Conference on Machine Learning (ICML) 2011.
Learning Scale Free Networks by Reweighted l1 Regularization;
Liu, Ihler; AI & Statistics 2010. (notable paper)
Negative Tree Reweighted Belief Propagation;
Liu, Ihler; Uncertainty in Artificial Intelligence (UAI), July 2010.
Particle Filtered MCMC-MLE with Connections to Contrastive Divergence;
Asuncion, Liu, Ihler, Smyth; Int'l Conf on Machine Learning (ICML), June 2010.
Learning with Blocks: Composite Likelihood and Contrastive Divergence;
Asuncion, Liu, Ihler, Smyth; AI & Statistics (AISTATS), April 2010.
Estimating Replicate Time-Shifts Using Gaussian Process Regression;
Liu, Lin, Anderson, Smyth, Ihler; Bioinformatics 26(6), Mar. 2010, pp. 770-776; doi:10.1093/bioinformatics/btq022.
Beihang University, Beijing, China, 2004-2008.
School of Advanced Engineering
B.S. in Information and Computation Science
University of California, Irvine, 2008-2009.
Graduate Program in Mathematical, Computational and Systems Biology
(photo gallery)
University of California, Irvine, 2009-Now.
Donald Bren School of Information and Computer Science
Pursuing Ph. D, advanced to candidacy in Mar 2011