Qiang Liu's Publications

Qiang Liu

Distributed Estimation, Information Loss and Exponential Families
Liu, Ihler; To Appear in Advances in Neural Information Processing Systems (NIPS) 2014.

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy
Zhou, Liu, Platt, Meek; International Conference on Machine Learning (ICML), June 2014. [Code] 

Marginal structured SVM with hidden variables
Ping, Liu, Ihler; International Conference on Machine Learning (ICML), June 2014.

Scoring Workers in Crowdsourcing: How Many Control Questions are Enough?
Liu, Ihler, Steyvers; Advances in Neural Information Processing Systems (NIPS) 2013.

Variational Planning for Graph-based MDPs;
Cheng, Liu, Chen, Ihler; Advances in Neural Information Processing Systems (NIPS) 2013.

Variational Algorithms for Marginal MAP;
Liu, Ihler; Journal of Machine Learning Research (JMLR) 2013.

Variational Inference for Crowdsourcing;
Liu, Peng, Ihler; Advances in Neural Information Processing Systems (NIPS) 2012. [Appendix, Code] 

Brain and muscle Arnt-like protein-1 (BMAL1) controls circadian cell proliferation and susceptibility to UVB-induced DNA damage in the epidermis;
Geyfman M, Kumar V, Liu Q, Ruiz R, Gordon W, Espitia F, Cam E, Millar SE, Smyth P, Ihler A, Takahashi JS, Andersen B; Proc Natl Acad Sci USA doi:10.1073/pnas.120959210 (2012). 

Belief Propagation for Structured Decision Making;
Liu, Ihler; Uncertainty in Artificial Intelligence (UAI) 2012. [Appendix] 

Distributed Parameter Estimation via Pseudo-likelihood;
Liu, Ihler; International Conference on Machine Learning (ICML) 2012. [Appendix] 

Computational Approaches to Sentence Completion;
Geoffrey Zweig, John C. Platt, Christopher Meek, Christopher J.C. Burges, Ainur Yessenalina, and Qiang Liu; in ACL 2012, ACL/SIGPARSE, July 2012.

Variational algorithms for marginal MAP;
Liu, Ihler; Uncertainty in Artificial Intelligence (UAI) 2011. [Full Version] 

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 award)

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.