| 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 | 1828 | 2012 |
| Challenges of big data analysis J Fan, F Han, H Liu National science review 1 (2), 293-314, 2014 | 1325 | 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 | 680 | 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 | 565 | 2009 |
| High-dimensional semiparametric Gaussian copula graphical models H Liu, F Han, M Yuan, J Lafferty, L Wasserman The Annals of Statistics 40 (4), 2293-2326, 2012 | 529 | 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 | 451 | 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 | 398 | 2012 |
| 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 | 368 | 2018 |
| 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 | 293 | 2016 |
| A general theory of hypothesis tests and confidence regions for sparse high dimensional models Y Ning, H Liu The Annals of Statistics 45 (1), 158-195, 2017 | 239 | 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 | 210 | 2009 |
| Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions M Wang, EX Fang, H Liu Mathematical Programming 161 (1), 419-449, 2017 | 180 | 2017 |
| 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 | 179 | 2014 |
| 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 | 157 | 2014 |
| A nonconvex optimization framework for low rank matrix estimation T Zhao, Z Wang, H Liu Advances in Neural Information Processing Systems 28, 2015 | 151 | 2015 |
| SpAM: Sparse Additive Models. P Ravikumar, H Liu, JD Lafferty, LA Wasserman NIPS, 1201-1208, 2007 | 150 | 2007 |
| Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging A Eloyan, J Muschelli, MB Nebel, H Liu, F Han, T Zhao, A Barber, S Joel, ... Frontiers in Systems Neuroscience 6, 2012 | 134 | 2012 |
| Forest density estimation H Liu, M Xu, H Gu, A Gupta, J Lafferty, L Wasserman Journal of Machine Learning Research 12, 907-951, 2011 | 132* | 2011 |
| TIGER: A Tuning-Insensitive Approach for Optimally Estimating Gaussian Graphical Models H Liu, L Wang arXiv preprint arXiv:1209.2437, 2012 | 116* | 2012 |
| Provable sparse tensor decomposition WW Sun, J Lu, H Liu, G Cheng Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017 | 113 | 2017 |
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
