• 3065 Citations
20042020

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2 Scopus citations

A convex formulation for high-dimensional sparse sliced inverse regression

Tan, K. M., Wang, Z., Zhang, T., Liu, H. & Cook, R. D., Dec 1 2018, In : Biometrika. 105, 4, p. 769-782 14 p.

Research output: Contribution to journalArticle

3 Scopus citations

A depression network of functionally connected regions discovered via multi-attribute canonical correlation graphs

Kang, J., Bowman, F. D. B., Mayberg, H. & Liu, H., Nov 1 2016, In : NeuroImage. 141, p. 431-441 11 p.

Research output: Contribution to journalArticle

6 Scopus citations

A direct estimation of high dimensional stationary vector autoregressions

Han, F., Lu, H. & Liu, H., Dec 1 2015, In : Journal of Machine Learning Research. 16, p. 3115-3150 36 p.

Research output: Contribution to journalArticle

21 Scopus citations

A framework for efficient association rule mining in XML data

Zhang, J., Liu, H., Ling, T. W., Bruckner, R. M. & Min Tjoa, A., Jan 1 2006, In : Journal of Database Management. 17, 3, p. 19-40 22 p.

Research output: Contribution to journalArticle

9 Scopus citations

A general theory of hypothesis tests and confidence regions for sparse high dimensional models

Ning, Y. & Liu, H., Feb 1 2017, In : Annals of Statistics. 45, 1, p. 158-195 38 p.

Research output: Contribution to journalArticle

39 Scopus citations

A likelihood ratio framework for high-dimensional semiparametric regression

Ning, Y., Zhao, T. & Liu, H., Dec 1 2017, In : Annals of Statistics. 45, 6, p. 2299-2327 29 p.

Research output: Contribution to journalArticle

10 Scopus citations

An Efficient Optimization Algorithm for Structured Sparse CCA, with Applications to eQTL Mapping

Chen, X. & Liu, H., May 1 2012, In : Statistics in Biosciences. 4, 1, p. 3-26 24 p.

Research output: Contribution to journalArticle

30 Scopus citations

A new perspective on robust M-estimation: Finite sample theory and applications to dependence-adjusted multiple testing

Zhou, W. X., Bose, K., Fan, J. & Liu, H., Oct 2018, In : Annals of Statistics. 46, 5, p. 1904-1931 28 p.

Research output: Contribution to journalArticle

6 Scopus citations

An extreme-value approach for testing the equality of large U-statistic based correlation matrices

Zhou, C., Han, F., Zhang, X. S. & Liu, H., May 2019, In : Bernoulli. 25, 2, p. 1472-1503 32 p.

Research output: Contribution to journalArticle

1 Scopus citations

An overview of the estimation of large covariance and precision matrices

Fan, J., Liao, Y. & Liu, H., Feb 1 2016, In : Econometrics Journal. 19, 1, p. C1-C32

Research output: Contribution to journalArticle

64 Scopus citations

A partially linear framework for massive heterogeneous data

Zhao, T., Cheng, G. & Liu, H., Jan 1 2016, In : Annals of Statistics. 44, 4, p. 1400-1437 38 p.

Research output: Contribution to journalArticle

36 Scopus citations

A semiparametric graphical modelling approach for large-scale equity selection

Liu, H., Mulvey, J. & Zhao, T., Jul 2 2016, In : Quantitative Finance. 16, 7, p. 1053-1067 15 p.

Research output: Contribution to journalArticle

1 Scopus citations

A strictly contractive Peace man Rachford splitting method for convex programming

He, B., Liu, H., Wang, Z. & Yuan, X., Jan 1 2014, In : SIAM Journal on Optimization. 24, 3, p. 1011-1040 30 p.

Research output: Contribution to journalArticle

59 Scopus citations

A unified theory of confidence regions and testing for high-dimensional estimating equations

Neykov, M., Ning, Y., Liu, J. S. & Liu, H., Aug 1 2018, In : Statistical Science. 33, 3, p. 427-443 17 p.

Research output: Contribution to journalArticle

9 Scopus citations

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

Eloyan, A., Muschelli, J., Nebel, M. B., Liu, H., Han, F., Zhao, T., Barber, A. D., Joel, S., Pekar, J. J., Mostofsky, S. H. & Caffo, B., Aug 30 2012, In : Frontiers in Systems Neuroscience. AUG 2012, p. 1-9 9 p.

Research output: Contribution to journalArticle

30 Scopus citations

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

Eloyan, A., Muschelli, J., Nebel, M. B., Liu, H., Han, F., Zhao, T., Barber, A., Joel, S., Pekar, J. J., Mostofsky, S. & Caffo, B., Jul 31 2012, In : Frontiers in Systems Neuroscience. JULY 2012

Research output: Contribution to journalArticle

42 Scopus citations

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach

Fang, E. X., Liu, H. & Wang, M., Jul 1 2019, In : Mathematical Programming. 176, 1-2, p. 175-205 31 p.

Research output: Contribution to journalArticle

Calibrated multivariate regression with application to neural semantic basis discovery

Liu, H., Wang, L. & Zhao, T., Aug 1 2015, In : Journal of Machine Learning Research. 16, p. 1579-1606 28 p.

Research output: Contribution to journalArticle

13 Scopus citations

Calibrated precision matrix estimation for high-dimensional elliptical distributions

Zhao, T. & Liu, H., Dec 1 2014, In : IEEE Transactions on Information Theory. 60, 12, p. 7884-7887 4 p., 6913534.

Research output: Contribution to journalArticle

12 Scopus citations

CODA: High dimensional Copula Discriminant Analysis

Han, F., Zhao, T. & Liu, H., Feb 1 2013, In : Journal of Machine Learning Research. 14, 1, p. 629-671 43 p.

Research output: Contribution to journalArticle

22 Scopus citations

Combinatorial inference for graphical models

Neykov, M., Lu, J. & Liu, H., Apr 2019, In : Annals of Statistics. 47, 2, p. 795-827 33 p.

Research output: Contribution to journalArticle

2 Scopus citations

Compressive network analysis

Jiang, X., Yao, Y., Liu, H. & Guibas, L., Nov 1 2014, In : IEEE Transactions on Automatic Control. 59, 11, p. 2946-2961 16 p., 6883133.

Research output: Contribution to journalArticle

1 Scopus citations

Distributed testing and estimation under sparse high dimensional models

Battey, H., Fan, J., Liu, H., Lu, J. & Zhu, Z., Jun 2018, In : Annals of Statistics. 46, 3, p. 1352-1382 31 p.

Research output: Contribution to journalArticle

14 Scopus citations

Distribution-free tests of independence in high dimensions

Han, F., Chen, S. & Liu, H., Dec 1 2017, In : Biometrika. 104, 4, p. 813-828 16 p.

Research output: Contribution to journalArticle

8 Scopus citations

ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions

Han, F. & Liu, H., Jan 2 2018, In : Journal of the American Statistical Association. 113, 521, p. 252-268 17 p.

Research output: Contribution to journalArticle

7 Scopus citations

Efficient, certifiably optimal clustering with applications to latent variable graphical models

Eisenach, C. & Liu, H., Jul 1 2019, In : Mathematical Programming. 176, 1-2, p. 137-173 37 p.

Research output: Contribution to journalArticle

1 Scopus citations

Forest density estimation

Liu, H., Xu, M., Gu, H., Gupta, A., Lafferty, J. & Wasserman, L., Mar 1 2011, In : Journal of Machine Learning Research. 12, p. 907-951 45 p.

Research output: Contribution to journalArticle

40 Scopus citations

Generalized alternating direction method of multipliers: new theoretical insights and applications

Fang, E. X., He, B., Liu, H. & Yuan, X., Jun 18 2015, In : Mathematical Programming Computation. 7, 2, p. 149-187 39 p.

Research output: Contribution to journalArticle

34 Scopus citations

Glmgraph: An R package for variable selection and predictive modeling of structured genomic data

Chen, L., Liu, H., Kocher, J. P. A., Li, H. & Chen, J., Jul 3 2015, In : Bioinformatics. 31, 24, p. 3991-3993 3 p.

Research output: Contribution to journalArticle

6 Scopus citations

Graph estimation from multi-attribute data

Kolar, M., Liu, H. & Xing, E. P., Jan 1 2014, In : Journal of Machine Learning Research. 15, p. 1713-1750 38 p.

Research output: Contribution to journalArticle

9 Scopus citations

Heterogeneity adjustment with applications to graphical model inference

Fan, J., Liu, H., Wang, W. & Zhu, Z., Jan 1 2018, In : Electronic Journal of Statistics. 12, 2, p. 3908-3952 45 p.

Research output: Contribution to journalArticle

Open Access

High-dimensional semiparametric bigraphical models

Ning, Y. & Liu, H., Sep 1 2013, In : Biometrika. 100, 3, p. 655-670 16 p.

Research output: Contribution to journalArticle

8 Scopus citations

High dimensional semiparametric latent graphical model for mixed data

Fan, J., Liu, H., Ning, Y. & Zou, H., Mar 1 2017, In : Journal of the Royal Statistical Society. Series B: Statistical Methodology. 79, 2, p. 405-421 17 p.

Research output: Contribution to journalArticle

25 Scopus citations

High Dimensional Semiparametric Scale-Invariant Principal Component Analysis

Han, F. & Liu, H., Oct 1 2014, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 36, 10, p. 2016-2032 17 p., 6747357.

Research output: Contribution to journalArticle

8 Scopus citations

How to draw the line in biomedical research

Huang, L., Rattner, A., Liu, H. & Nathans, J., Mar 19 2013, In : eLife. 2013, 2, e00638.

Research output: Contribution to journalArticle

3 Scopus citations

Identifying economic regimes: Reducing downside risks for university endowments and foundations

Mulvey, J. M. & Liu, H., Sep 1 2016, In : Journal of Portfolio Management. 43, 1, p. 100-108 9 p.

Research output: Contribution to journalArticle

2 Scopus citations

I-LAMM for sparse learning: Simultaneous control of algorithmic complexity and statistical error

Fan, J., Liu, H., Sun, Q. & Zhang, T., Apr 2018, In : Annals of Statistics. 46, 2, p. 814-841 28 p.

Research output: Contribution to journalArticle

11 Scopus citations

Implementation of an interorganizational system: The case of medical insurance e-clearance

Bose, I., Liu, H. & Ye, A., Mar 1 2012, In : Journal of Information Systems Education. 23, 1, p. 29-39 11 p.

Research output: Contribution to journalArticle

1 Scopus citations

Joint estimation of multiple graphical models from high dimensional time series

Qiu, H., Han, F., Liu, H. & Caffo, B., Mar 1 2016, In : Journal of the Royal Statistical Society. Series B: Statistical Methodology. 78, 2, p. 487-504 18 p.

Research output: Contribution to journalArticle

27 Scopus citations

Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model

Lu, J., Kolar, M. & Liu, H., Jan 1 2020, (Accepted/In press) In : Journal of the American Statistical Association.

Research output: Contribution to journalArticle

Large covariance estimation through elliptical factor models

Fan, J., Liu, H. & Wang, W., Aug 2018, In : Annals of Statistics. 46, 4, p. 1383-1414 32 p.

Research output: Contribution to journalArticle

10 Scopus citations

Layer-wise learning strategy for nonparametric tensor product smoothing spline regression and graphical models

Tan, K. M., Lu, J., Zhang, T. & Liu, H., Aug 1 2019, In : Journal of Machine Learning Research. 20

Research output: Contribution to journalArticle

Max-norm optimization for robust matrix recovery

Fang, E. X., Liu, H., Toh, K. C. & Zhou, W. X., Jan 1 2018, In : Mathematical Programming. 167, 1, p. 5-35 31 p.

Research output: Contribution to journalArticle

1 Scopus citations

Mining historic query trails to label long and rare search engine queries

Bailey, P., White, R. W., Liu, H. & Kumaran, G., Sep 1 2010, In : ACM Transactions on the Web. 4, 4, 15.

Research output: Contribution to journalArticle

24 Scopus citations

Mining Massive Amounts of Genomic Data: A Semiparametric Topic Modeling Approach

Fang, E. X., Li, M. D., Jordan, M. I. & Liu, H., Jul 3 2017, In : Journal of the American Statistical Association. 112, 519, p. 921-932 12 p.

Research output: Contribution to journalArticle

3 Scopus citations

Near-optimal stochastic approximation for online principal component estimation

Li, C. J., Wang, M., Liu, H. & Zhang, T., Jan 1 2018, In : Mathematical Programming. 167, 1, p. 75-97 23 p.

Research output: Contribution to journalArticle

11 Scopus citations

On efficient and effective association rule mining from XML data

Zhang, J., Ling, T. W., Bruckner, R. M., Tjoa, A. M. & Liu, H., Dec 1 2004, In : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3180, p. 497-507 11 p.

Research output: Contribution to journalArticle

9 Scopus citations

On faster convergence of cyclic block coordinate descent-type methods for strongly convex minimization

Li, X., Zhao, T., Arora, R., Liu, H. & Hong, M., Apr 1 2018, In : Journal of Machine Learning Research. 18, p. 1-24 24 p.

Research output: Contribution to journalArticle