Han Liu
Han Liu
Orrington Lunt Professor of Computer Science, Statistics and Data Science, Northwestern University
Verified email at - Homepage
Cited by
Cited by
Patterns and rates of exonic de novo mutations in autism spectrum disorders
BM Neale, Y Kou, L Liu, A Ma’ayan, KE Samocha, A Sabo, CF Lin, ...
Nature 485, 242-245, 2012
Challenges of big data analysis
J Fan, F Han, H Liu
National science review 1 (2), 293-314, 2014
The nonparanormal: Semiparametric estimation of high dimensional undirected graphs
H Liu, J Lafferty, L Wasserman
The Journal of Machine Learning Research 10, 2295-2328, 2009
Sparse additive models
P Ravikumar, J Lafferty, H Liu, L Wasserman
Journal of the Royal Statistical Society: Series B 75 (5), 1009-1030, 2009
Fully decentralized multi-agent reinforcement learning with networked agents
K Zhang, Z Yang, H Liu, T Zhang, T Basar
International conference on machine learning, 5872-5881, 2018
High-dimensional semiparametric Gaussian copula graphical models
H Liu, F Han, M Yuan, J Lafferty, L Wasserman
Stability approach to regularization selection (stars) for high dimensional graphical models
H Liu, K Roeder, L Wasserman
Advances in Neural Information Processing Systems 23, 1432-1440, 2010
The huge package for high-dimensional undirected graph estimation in R
T Zhao, H Liu, K Roeder, J Lafferty, L Wasserman
The Journal of Machine Learning Research 13 (1), 1059-1062, 2012
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Y Ji, Z Zhou, H Liu, RV Davuluri
Bioinformatics 37 (15), 2112-2120, 2021
An overview of the estimation of large covariance and precision matrices
J Fan, Y Liao, H Liu
The Econometrics Journal 19 (1), C1-C32, 2016
A general theory of hypothesis tests and confidence regions for sparse high dimensional models
Y Ning, H Liu
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions
M Wang, EX Fang, H Liu
Mathematical Programming 161, 419-449, 2017
Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery
H Liu, M Palatucci, J Zhang
Proceedings of the 26th annual international conference on machine learning …, 2009
Distributed testing and estimation under sparse high dimensional models
H Battey, J Fan, H Liu, J Lu, Z Zhu
Annals of statistics 46 (3), 1352, 2018
Optimal computational and statistical rates of convergence for sparse nonconvex learning problems
Z Wang, H Liu, T Zhang
Annals of statistics 42 (6), 2164, 2014
Parametrized deep q-networks learning: Reinforcement learning with discrete-continuous hybrid action space
J Xiong, Q Wang, Z Yang, P Sun, L Han, Y Zheng, H Fu, T Zhang, J Liu, ...
arXiv preprint arXiv:1810.06394, 2018
A strictly contractive peaceman--rachford splitting method for convex programming
B He, H Liu, Z Wang, X Yuan
SIAM Journal on Optimization 24 (3), 1011-1040, 2014
Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network
Y Hou, W Che, Y Lai, Z Zhou, Y Liu, H Liu, T Liu
arXiv preprint arXiv:2006.05702, 2020
A gut commensal bacterium promotes mosquito permissiveness to arboviruses
P Wu, P Sun, K Nie, Y Zhu, M Shi, C Xiao, H Liu, Q Liu, T Zhao, X Chen, ...
Cell host & microbe 25 (1), 101-112. e5, 2019
A nonconvex optimization framework for low rank matrix estimation
T Zhao, Z Wang, H Liu
Advances in Neural Information Processing Systems 28, 2015
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