Han Liu, Ph.D.
Affiliations: | 2010 | Carnegie Mellon University, Pittsburgh, PA |
Area:
Computer Science, StatisticsGoogle:
"Han Liu"Parents
Sign in to add mentor| Larry Wasserman | grad student | 2010 | Carnegie Mellon | |
| (Nonparametric Learning in High Dimensions.) | ||||
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Publications
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| Lyu X, Sun WW, Wang Z, et al. (2019) Tensor Graphical Model: Non-convex Optimization and Statistical Inference. Ieee Transactions On Pattern Analysis and Machine Intelligence |
| Zhou WX, Bose K, Fan J, et al. (2018) A NEW PERSPECTIVE ON ROBUST -ESTIMATION: FINITE SAMPLE THEORY AND APPLICATIONS TO DEPENDENCE-ADJUSTED MULTIPLE TESTING. Annals of Statistics. 46: 1904-1931 |
| Battey H, Fan J, Liu H, et al. (2018) DISTRIBUTED TESTING AND ESTIMATION UNDER SPARSE HIGH DIMENSIONAL MODELS. Annals of Statistics. 46: 1352-1382 |
| Neykov M, Ning Y, Liu JS, et al. (2018) A Unified Theory of Confidence Regions and Testing for High-Dimensional Estimating Equations Statistical Science. 33: 427-443 |
| Li CJ, Wang M, Liu H, et al. (2018) Near-optimal stochastic approximation for online principal component estimation Mathematical Programming. 167: 75-97 |
| Han F, Liu H. (2017) Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution. Bernoulli : Official Journal of the Bernoulli Society For Mathematical Statistics and Probability. 23: 23-57 |
| Liu H, Wang L. (2017) TIGER: A tuning-insensitive approach for optimally estimating gaussian graphical models Electronic Journal of Statistics. 11: 241-294 |
| Ning Y, Zhao T, Liu H. (2017) A likelihood ratio framework for high-dimensional semiparametric regression The Annals of Statistics. 45: 2299-2327 |
| Sun WW, Lu J, Liu H, et al. (2017) Provable sparse tensor decomposition Journal of the Royal Statistical Society Series B-Statistical Methodology. 79: 899-916 |
| Fang EX, Li M, Jordan MI, et al. (2017) Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach Journal of the American Statistical Association. 112: 921-932 |