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All publications by Han Liu
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Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes
Huitong Qiu, Sheng Xu, Fang Han, Han Liu and Brian Caffo
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimal Linear Estimation under Unknown Nonlinear Transform
Xinyang Yi, Zhaoran Wang, Constantine Caramanis and Han Liu
Advances in Neural Information Processing Systems 28, 2015


Non-convex Statistical Optimization for Sparse Tensor Graphical Model
Wei Sun, Zhaoran Wang, Han Liu and Guang Cheng
Advances in Neural Information Processing Systems 28, 2015


High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality
Zhaoran Wang, Quanquan Gu, Yang Ning and Han Liu
Advances in Neural Information Processing Systems 28, 2015


Local Smoothness in Variance Reduced Optimization
Daniel Vainsencher, Han Liu and Tong Zhang
Advances in Neural Information Processing Systems 28, 2015


A Nonconvex Optimization Framework for Low Rank Matrix Estimation
Tuo Zhao, Zhaoran Wang and Han Liu
Advances in Neural Information Processing Systems 28, 2015


Robust Portfolio Optimization
Huitong Qiu, Fang Han, Han Liu and Brian Caffo
Advances in Neural Information Processing Systems 28, 2015


Multivariate Regression with Calibration
Han Liu, Lie Wang and Tuo Zhao
Advances in Neural Information Processing Systems 27, 2014


Sparse PCA with Oracle Property
Quanquan Gu, Zhaoran Wang and Han Liu
Advances in Neural Information Processing Systems 27, 2014


Accelerated Mini-batch Randomized Block Coordinate Descent Method
Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora and Han Liu
Advances in Neural Information Processing Systems 27, 2014


Mode Estimation for High Dimensional Discrete Tree Graphical Models
Chao Chen, Han Liu, Dimitris Metaxas and Tianqi Zhao
Advances in Neural Information Processing Systems 27, 2014


Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time
Zhaoran Wang, Huanran Lu and Han Liu
Advances in Neural Information Processing Systems 27, 2014


Markov Network Estimation From Multi-attribute Data
Mladen Kolar, Han Liu and Eric Xing
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Transition Matrix Estimation in High Dimensional Time Series
Fang Han and Han Liu
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Sparse Inverse Covariance Estimation with Calibration
Tuo Zhao and Han Liu
Advances in Neural Information Processing Systems 26, 2013


Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model
Fang Han and Han Liu
Advances in Neural Information Processing Systems 26, 2013


Feature Selection in High-Dimensional Classification
Mladen Kolar and Han Liu
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Principal Component Analysis on non-Gaussian Dependent Data
Fang Han and Han Liu
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Exponential Concentration for Mutual Information Estimation with Application to Forests
Han Liu, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 25, 2012


Transelliptical Graphical Models
Han Liu, Fang Han and Cun-hui Zhang
Advances in Neural Information Processing Systems 25, 2012


Transelliptical Component Analysis
Fang Han and Han Liu
Advances in Neural Information Processing Systems 25, 2012


Semiparametric Principal Component Analysis
Fang Han and Han Liu
Advances in Neural Information Processing Systems 25, 2012


Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation
Tuo Zhao, Kathryn Roeder and Han Liu
Advances in Neural Information Processing Systems 25, 2012


The Nonparanormal SKEPTIC
Han Liu, Fang Han, Ming Yuan, Larry Wasserman and John D. Lafferty
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Sparse Additive Machine
Tuo Zhao and Han Liu
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Marginal Regression For Multitask Learning
Mladen Kolar and Han Liu
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Detecting Network Cliques with Radon Basis Pursuit
Xiaoye Jiang, Yuan Yao, Han Liu and Leonidas J. Guibas
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Structured Sparse Canonical Correlation Analysis
Xi Chen, Han Liu and Jaime G. Carbonell
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
Han Liu, Kathryn Roeder and Larry Wasserman
Advances in Neural Information Processing Systems 23, 2010


Graph-Valued Regression
Han Liu, Xi Chen, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 23, 2010


Multivariate Dyadic Regression Trees for Sparse Learning Problems
Han Liu and Xi Chen
Advances in Neural Information Processing Systems 23, 2010


The Group Dantzig Selector
Han Liu, Jian Zhang, Xiaoye Jiang and Jun Liu
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John D. Lafferty and Larry A. Wasserman
Journal of Machine Learning Research, 2009


Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery
Han Liu, Mark Palatucci and Jian Zhang
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Nonparametric Greedy Algorithms for the Sparse Learning Problem
Han Liu and Xi Chen
Advances in Neural Information Processing Systems 22, 2009


Estimation Consistency of the Group Lasso and its Applications
Han Liu and Jian Zhang
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Nonparametric regression and classification with joint sparsity constraints
Han Liu, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 21, 2008


SpAM: Sparse Additive Models
Han Liu, Larry Wasserman, John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 20, 2007


Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo
Han Liu, John D. Lafferty and Larry A. Wasserman
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007