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 | 2088 | 2012 |
Challenges of big data analysis J Fan, F Han, H Liu National science review 1 (2), 293-314, 2014 | 1916 | 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 | 893 | 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 | 853 | 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 | 715 | 2018 |
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 | 691 | 2021 |
High-dimensional semiparametric Gaussian copula graphical models H Liu, F Han, M Yuan, J Lafferty, L Wasserman | 646 | 2012 |
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 | 592 | 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 | 573 | 2012 |
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 | 448 | 2016 |
A general theory of hypothesis tests and confidence regions for sparse high dimensional models Y Ning, H Liu | 369 | 2017 |
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions M Wang, EX Fang, H Liu Mathematical Programming 161, 419-449, 2017 | 282 | 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 | 229 | 2009 |
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 | 225 | 2018 |
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 | 223 | 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 | 209 | 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 | 205 | 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 | 200 | 2019 |
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 | 199 | 2014 |
A nonconvex optimization framework for low rank matrix estimation T Zhao, Z Wang, H Liu Advances in Neural Information Processing Systems 28, 2015 | 174 | 2015 |