TIGER: A Tuning-Insensitive Approach for Optimal Graph Estimation
Han Liu and Lie Wang
On the arXiv:1209.2437. 2012.
Multivariate Regression with Calibration
Han Liu, Lie Wang, and Tuo Zhao
On the arXiv:1305.2238. 2013.
Optimal Rates of Convergence of Transelliptical Component Analysis
Fang Han and Han Liu
On the arXiv:1305.6916. 2013.
Graph Estimation From Multi-attribute Data
Mladen Kolar, Han Liu, and Eric Xing
On the arXiv:1210.7665. 2012.
Optimal Tests of Treatment Effects Using Sparse Linear Programming
Michael Rosenblum, Han Liu, and En-Hsu Yen
On the arXiv:1306.0964. 2013.
Compressive Network Analysis
Xiaoye Jiang, Yuan Yao, Han Liu, and Leonidas Guibas
IEEE Transactions on Automatic Control. To appear. 2013.
Statistical Analysis of Big Data on Pharmacogenomics
Jianqing Fan and Han Liu
Advanced Drug Delivery Reviews. To appear. 2013.
Discussion on ‘Large covariance estimation by thresholding principal orthogonal complements’
Han Liu and Lie Wang
Journal of the Royal Statistical Society: Series B (Statistical Methodology) (JRSSB). To appear. 2013.
CODA: Copula Discriminant Analysis
Fang Han, Tuo Zhao, and Han Liu
Journal of Machine Learning Research (JMLR). Volume 14, pp629-671. 2013.
High Dimensional Semiparametric Bigraphical Model
Yang Ning and Han Liu
Biometrika. To appear. 2013.
Sparse Covariance Matrix Estimation with Eigenvalue Constraints
Han Liu, Lie Wang, and Tuo Zhao
Journal of Computational and Graphical Statistics (JCGS). To appear. 2013.
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series
Zhaoran Wang, Fang Han, and Han Liu
Journal of Machine Learning Research (AISTATS track). To appear. 2013 (Winner of the Notable Paper Award)
Transition Matrix Estimation in High Dimensional Vector Autoregressive Models
Fang Han and Han Liu
International Conference on Machine Learning (ICML). To appear. 2013.
Principal Componenet Analysis on non-Gaussian Dependent Data
Fang Han and Han Liu
International Conference on Machine Learning (ICML). To appear. 2013. (Winner of the 2013 ENAR Distinguished Student Paper Award)
Feature Selection in High-Dimensional Classification
Mladen Kolar and Han Liu
International Conference on Machine Learning (ICML). To appear. 2013.
Graph Estimation From Multi-attribute Data
Mladen Kolar, Han Liu and Eric Xing
International Conference on Machine Learning (ICML). To appear. 2013.
Automated Diagnoses of Attention Defficit Hyperactive Disorder using MRI
with Ani Eloyan et al.
Frontiers in Systems Neuroscience, Volume 6, No. 61, 2012. (Winner of the the ADHD-200 Global Competition for achieving the Highest Prediction Performance of Imaging- Based Diagnostic Classification Algorithm)
High Dimensional Semiparametric Gaussian Copula Graphical Models
Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry Wasserman
The Annals of Statistics, Volume 40, No. 40, pp2293-2326. 2012. (Winner of the David P. Byar Young Investigator Travel Award sponsered by ASA Biometrics section)
Sparse Nonparametric Graphical Models
John Lafferty, Han Liu, and Larry Wasserman
Statistical Science, Volume 27, No 4, pp519-537. 2012.
Exponential Concentration Inequality for Mutual Information Estimation
Han Liu, John Lafferty and Larry Wasserman
Neural Information Processing Systems (NIPS), 25, 2012.
High Dimensional Transelliptical Graphical Models
Han Liu, Fang Han and Cun-hui Zhang
Neural Information Processing Systems (NIPS), 25, 2012.
Transelliptical Principal Component Analysis for non-Gaussian Data
Fang Han and Han Liu
Neural Information Processing Systems (NIPS), 25, 2012.
Transelliptical Component Analysis
Fang Han and Han Liu
Neural Information Processing Systems (NIPS), 25, 2012.
Nonparanormal Graph Estimation via Smooth-projected Neighborhood Pursuit
Tuo Zhao, Kathryn Roeder and Han Liu
Neural Information Processing Systems (NIPS), 25, 2012.
Patterns and Rates of Exonic de novo Mutations in Autism Spectrum Disorders
with Benjamin M. Neale et al.
Nature,485, pp242-245. 2012. (News from New York Times)
An Efficient Optimization Algorithm for Structured Sparse CCA, with Applications to eQTL Mapping
Xi Chen and Han Liu
Statistics in Biosciences, Vol 4, No 1, pp3-26. 2012.
HUGE: High Dimensional Undirected Graph Estimation
Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, and Larry Wasserman
Journal of Machine Learning Research (JMLR), Vol 3, pp1059-1062. 2012.
Marginal Regression For Multitask Learning
Mladen Kolar and Han Liu
Journal of Machine Learning Research (AISTATS track), WCP Vol 22, pp647-655, 2012.
Sparse Additive Machine
Tuo Zhao and Han Liu
Journal of Machine Learning Research (AISTATS track), WCP Vol 22, pp1435-1443, 2012.
Structured Sparse Canonical Correlation Analysis
Xi Chen and Han Liu
Journal of Machine Learning Research (AISTATS track), WCP Vol 22, pp199-207, 2012.
Network Clique Detection using Radon Basis Pursuit
Xiaoye Jiang, Yuan Yao, Han Liu, and Leo Guibas
Journal of Machine Learning Research (AISTATS track), WCP Vol 22, pp565-573, 2012.
The Nonparanormal SKEPTIC
Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry Wasserman
International Conference on Machine Learning (ICML), 2012.
Forest Density Estimation
Han Liu, Min Xu, Haijie Gu, Anupam Dasgupta, John Lafferty, and Larry Wasserman
Journal of Machine Learning Research (JMLR) Vol 12, 907−951. 2011.
Stability Approach to Regularization Selection (StARS) for High-Dim Graphical Models
Han Liu, Kathryn Roeder and Larry Wasserman
Neural Information Processing Systems (NIPS), 23, 2010.
Graph-Valued Regression
Han Liu, Xi Chen, John Lafferty, and Larry Wasserman
Neural Information Processing Systems (NIPS), 23, 2010.
Multivariate Dyadic Regression Trees for Sparse Learning Problems
Han Liu and Xi Chen
Neural Information Processing Systems (NIPS), 23, 2010. (Winner of the 2010 ASA Student Paper Competition sponsored by the Statistical Computing Section)
Mining Past Query Trails to Label Long and Rare Search Engine Queries
Peter Bailey, Ryen W. White, Han Liu, and Giridhar Kumaran
ACM Transactions on the Web (ACM TWEB) 1(2) 1-25, 2010.
The Group Dantzig Selector
Han Liu, Jian Zhang, Xiaoye Jiang, and Jun Liu
Journal of Machine Learning Research (JMLR), WCP Volume 9, pp461-468, 2010.
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis
Xi Chen, Yan Liu, Han Liu and Jaime G. Carbonell
The Twenty-Fourth Conference on Artificial Intelligence (AAAI), 2010.
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John Lafferty, and Larry Wasserman
Journal of Machine Learning Research (JMLR), (10) 2295-2328, 2009.
Nonparametric Greedy Algorithm for the Sparse Learning Problems
Han Liu and Xi Chen
Neural Information Processing Systems (NIPS), 22, 2009.
Blockwise Coordinate Descent Procedures for the Multi-task Lasso
Han Liu, Mark Palatucci, and Jian Zhang
The Twenty-sixth International Conference on Machine Learning (ICML), 2009. (Winner of the Best Student Paper Award and Best Overall Paper Honorable Mention)
On the Estimation Consistency of the Group Lasso and its Applications
Han Liu and Jian Zhang
Journal of Machine Learning Research (AISTATS track), WCP-Volume 5:pp376-383, 2009. (Best Paper Award Nominee at AISTATS's 09)
Sparse Additive Models
Pradeep Ravikumar, John Lafferty, Han Liu, Larry Wasserman
Journal of the Royal Statistical Society: Series B (Statistical Methodology) (JRSSB), 2009.
On the Estimation and Variable Selection Consistency of the Bock q-norm Regression
Han Liu and Jian Zhang
Technical Report, Department of Statistics, Carnegie Mellon University (CMU-STAT-TR-86), 2009.
Some Two-step Procedures for Variable Selection in High-dimensional Linear Regression
Jian Zhang, Jessie Jeng, and Han Liu
Technical Report, Department of Statistics, Purdue University (Purdue-STAT-TR-08-05), 2009.
Nonparametric Regression and Classification with Joint Sparsity Constraints
Han Liu, John Lafferty, and Larry Wasserman
Neural Information Processing Systems (NIPS), 21, 2008.
Neural Semantic Basis Discovery using Simultaneous Sparse Approximation
Mark Palatucci, Tom Mitchell, and Han Liu
Sparse Optimization and Variable Selection Workshop (ICML), 2008.
SpAM: Sparse Additive Models
Pradeep Ravikumar, Han Liu, John Lafferty and Larry Wasserman
Neural Information Processing Systems (NIPS), 20, 2007.
Sparse Nonparametric Density Estimation in High Dimensions using the Rodeo
Han Liu, John Lafferty, and Larry Wasserman
Journal of Machine Learning Research (AISTATS track), WCP-Volume 2:283-290, 2007.
Towards the Prediction of Protein Abundance from Tandem Mass Spectrometry Data
Anthony Bonner and Han Liu
The Sixth SIAM International Conference on Data Mining (SDM), 2006.
A Framework for Efficient Association Rule Mining in XML Data
Ji Zhang, Han Liu, Tok Wang Ling, Robert M.Bruckner, and A. Min Tjoa
Journal of Database Management (JDM). pp19-40 Volume 17 Issue 3, 2006.
Canonical Correlation, an Approximation, and the Prediction of Protein Abundance
Anthony Bonner and Han Liu
The Eighth Workshop on Mining Scientific and Engineering Datasets (MSD), 2005.
A Generalized Real-Time Obstacle Avoidance Method Without the Cspace Calculation
Yong-Ji Wang, Matthew Cartmell, Qiu-Ming Tao, Han Liu
Journal of Computer Science and Technology (JCST), Volume 20(6): 774-787, 2005.
D-GridMST: Clustering Large Distributed Spatial Databases
Ji Zhang and Han Liu
Book Chapter of Classification and Clustering for Knowledge Discovery. Springer-Verlag Publisher, ISBN 978-3-540-26073-8, 2005.
Dimension Reduction with Penalized Independent Component Analysis
Han Liu and Rafal Kustra
The NIPS workshop on New Problems and Methods in Computational Biology (NIPS), 2005.
Predicting Protein Levels from Tandem Mass Spectrometry Data
Anthony Bonner and Han Liu
The NIPS workshop on New Problems and Methods in Computational Biology (NIPS), 2005.
Comparison of Discrimination Methods for Peptide Classification in MS/MS
Anthony Bonner and Han Liu
IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), 2004.
Modeling Protein MS/MS Data with an Extended Linear Regression Strategy
Han Liu, Anthony Bonner, and Andrew Emily
The Twenty-sixth Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), 2004.
An Efficient Method to Estimate Labeled Sample Size for Transductive LDA(QDA/MDA)
Han Liu, Xiaobin Yuan, Qianying Tang, and Rafal Kustra
The Fifteenth European Conference on Machine Learning (ECML), 2004
A Realistic Method for Real-time Obstacle Avoidance
Han Liu and Yongji Wang
IEEE International Conference on Robotics and Automaton (IEEE RAM), 2004.
A Real-time Robot Path Planning Approach without the Computation of Cspace Obstacles
Yongji Wang, Han Liu, Qing Wang, Mingshu Li, Jinhui Zhou and M. Cartmell
Journal of Robotica. pp173-187 Volume 22 Issue 2, 2004.
