Heng Lian

According to our database, Heng Lian authored at least 89 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Statistical performance of quantile tensor regression with convex regularization.

Wenqi Lu, Zhongyi Zhu, Rui Li, Heng Lian

J. Multivar. Anal., March, 2024

2023

On Optimal Learning With Random Features.

Jiamin Liu, Heng Lian

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Communication-efficient estimation of quantile matrix regression for massive datasets.

Yaohong Yang, Lei Wang, Jiamin Liu, Rui Li, Heng Lian

Comput. Stat. Data Anal., November, 2023

Value iteration for streaming data on a continuous space with gradient method in an RKHS.

Jiamin Liu, Wangli Xu, Yue Wang, Heng Lian

Neural Networks, September, 2023

Properties of Standard and Sketched Kernel Fisher Discriminant.

Jiamin Liu, Wangli Xu, Fode Zhang, Heng Lian

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Semiparametric function-on-function quantile regression model with dynamic single-index interactions.

Hanbing Zhu, Yuanyuan Zhang, Yehua Li, Heng Lian

Comput. Stat. Data Anal., June, 2023

Image recognition and classification with HOG based on nonlinear support tensor machine.

Chunyang Zhu, Weihua Zhao, Heng Lian

Multim. Tools Appl., May, 2023

Best subset selection for high-dimensional non-smooth models using iterative hard thresholding.

Yue Wang, Wenqi Lu, Heng Lian

Inf. Sci., May, 2023

On Linear Convergence of ADMM for Decentralized Quantile Regression.

Yue Wang, Heng Lian

IEEE Trans. Signal Process., 2023

Functional additive expectile regression in the reproducing kernel Hilbert space.

Yuzi Liu, Ling Peng, Qing Liu, Heng Lian, Xiaohui Liu

J. Multivar. Anal., 2023

Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions.

Brittany Green, Heng Lian, Yan Yu, Tianhai Zu

J. Multivar. Anal., 2023

2022

Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification.

Yingying Zhang, Yan-Yong Zhao, Heng Lian

J. Mach. Learn. Res., 2022

Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions.

Shaogao Lv, Heng Lian

J. Mach. Learn. Res., 2022

Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes.

Zhuye Jie, Chen Chen, Lilan Hao, Fei Li, Liju Song, Xiaowei Zhang, Jie Zhu, Liu Tian, Xin Tong, Kaiye Cai, Zhe Zhang, Yanmei Ju, Xinlei Yu, Ying Li, Hongcheng Zhou, Haorong Lu, Xuemei Qiu, Qiang Li, Yunli Liao, Dongsheng Zhou, Heng Lian, Yong Zuo, Xiaomin Chen, Weiqiao Rao, Yan Ren, Yuan Wang, Jin Zi, Rong Wang, Na Liu, Jinghua Wu, Wei Zhang, Xiao Liu, Yang Zong, Weibin Liu, Liang Xiao, Yong Hou, Xun Xu, Huanming Yang, Jian Wang, Karsten Kristiansen, Huijue Jia

Genom. Proteom. Bioinform., 2022

Sparse high-dimensional semi-nonparametric quantile regression in a reproducing kernel Hilbert space.

Yue Wang, Yan Zhou, Rui Li, Heng Lian

Comput. Stat. Data Anal., 2022

Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space.

Heng Lian

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Deep Learning from Doubly-Streaming Data.

Heng Lian, John Scovil Atwood, Bojian Hou, Jian Wu, Yi He

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

2021

Distributed Partially Linear Additive Models With a High Dimensional Linear Part.

Yue Wang, Weiping Zhang, Heng Lian

IEEE Trans. Signal Inf. Process. over Networks, 2021

Learning Rate for Convex Support Tensor Machines.

Heng Lian

IEEE Trans. Neural Networks Learn. Syst., 2021

Distributed learning for sketched kernel regression.

Heng Lian, Jiamin Liu, Zengyan Fan

Neural Networks, 2021

Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces.

Guangren Yang, Xiaohui Liu, Heng Lian

J. Complex., 2021

Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection.

Fode Zhang, Rui Li, Heng Lian

Inf. Sci., 2021

Sketched quantile additive functional regression.

Yingying Zhang, Heng Lian

Neurocomputing, 2021

2020

Debiasing and Distributed Estimation for High-Dimensional Quantile Regression.

Weihua Zhao, Fode Zhang, Heng Lian

IEEE Trans. Neural Networks Learn. Syst., 2020

Randomized sketches for kernel CCA.

Heng Lian, Fode Zhang, Wenqi Lu

Neural Networks, 2020

Nonlinear functional canonical correlation analysis via distance covariance.

Hanbing Zhu, Rui Li, Riquan Zhang, Heng Lian

J. Multivar. Anal., 2020

Randomized sketches for sparse additive models.

Fode Zhang, Xuejun Wang, Rui Li, Heng Lian

Neurocomputing, 2020

A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model.

Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu

Comput. Stat. Data Anal., 2020

Partially functional linear regression in reproducing kernel Hilbert spaces.

Xia Cui, Hongmei Lin, Heng Lian

Comput. Stat. Data Anal., 2020

2019

Estimation and testing for partially functional linear errors-in-variables models.

Hanbing Zhu, Riquan Zhang, Zhou Yu, Heng Lian, Yanghui Liu

J. Multivar. Anal., 2019

Rank reduction for high-dimensional generalized additive models.

Hongmei Lin, Heng Lian, Hua Liang

J. Multivar. Anal., 2019

Reduced rank modeling for functional regression with functional responses.

Hongmei Lin, Xuejun Jiang, Heng Lian, Weiping Zhang

J. Multivar. Anal., 2019

Regression adjustment for treatment effect with multicollinearity in high dimensions.

Lili Yue, Gaorong Li, Heng Lian, Xiang Wan

Comput. Stat. Data Anal., 2019

Estimation for single-index models via martingale difference divergence.

Jicai Liu, Peirong Xu, Heng Lian

Comput. Stat. Data Anal., 2019

Pursuit of dynamic structure in quantile additive models with longitudinal data.

Xia Cui, Weihua Zhao, Heng Lian, Hua Liang

Comput. Stat. Data Anal., 2019

2018

On the sign consistency of the Lasso for the high-dimensional Cox model.

Shaogao Lv, Mengying You, Huazhen Lin, Heng Lian, Jian Huang

J. Multivar. Anal., 2018

Quantile regression for additive coefficient models in high dimensions.

Zengyan Fan, Heng Lian

J. Multivar. Anal., 2018

Time-varying quantile single-index model for multivariate responses.

Weihua Zhao, Yan Zhou, Heng Lian

Comput. Stat. Data Anal., 2018

A principal varying-coefficient model for quantile regression: Joint variable selection and dimension reduction.

Weihua Zhao, Xuejun Jiang, Heng Lian

Comput. Stat. Data Anal., 2018

Estimation and testing for time-varying quantile single-index models with longitudinal data.

Jianbo Li, Heng Lian, Xuejun Jiang, Xinyuan Song

Comput. Stat. Data Anal., 2018

2017

Quantile index coefficient model with variable selection.

Weihua Zhao, Heng Lian

J. Multivar. Anal., 2017

Estimation and variable selection for quantile partially linear single-index models.

Yuankun Zhang, Heng Lian, Yan Yu

J. Multivar. Anal., 2017

Estimation and model identification of longitudinal data time-varying nonparametric models.

Shu Liu, Jinhong You, Heng Lian

J. Multivar. Anal., 2017

Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models.

Yujie Li, Gaorong Li, Heng Lian, Tiejun Tong

J. Multivar. Anal., 2017

Divide-and-Conquer for Debiased $l_1$-norm Support Vector Machine in Ultra-high Dimensions.

Heng Lian, Zengyan Fan

J. Mach. Learn. Res., 2017

Composite quantile regression for correlated data.

Weihua Zhao, Heng Lian, Xinyuan Song

Comput. Stat. Data Anal., 2017

2016

Mean and quantile boosting for partially linear additive models.

Xingyu Tang, Heng Lian

Stat. Comput., 2016

Separation of linear and index covariates in partially linear single-index models.

Heng Lian, Hua Liang

J. Multivar. Anal., 2016

Nonconvex penalized reduced rank regression and its oracle properties in high dimensions.

Heng Lian, Yongdai Kim

J. Multivar. Anal., 2016

Posterior convergence for Bayesian functional linear regression.

Heng Lian, Taeryon Choi, Jie Meng, Seongil Jo

J. Multivar. Anal., 2016

Minimax convergence rates for kernel CCA.

Zengyan Fan, Heng Lian

J. Multivar. Anal., 2016

Estimation and variable selection for proportional response data with partially linear single-index models.

Weihua Zhao, Heng Lian, Riquan Zhang, Peng Lai

Comput. Stat. Data Anal., 2016

The Expectation-Maximization approach for Bayesian quantile regression.

Kaifeng Zhao, Heng Lian

Comput. Stat. Data Anal., 2016

Robust closed-form estimators for the integer-valued GARCH (1, 1) model.

Qi Li, Heng Lian, Fukang Zhu

Comput. Stat. Data Anal., 2016

Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach.

Sanying Feng, Heng Lian, Fukang Zhu

Comput. Stat. Data Anal., 2016

A new nested Cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data.

Sanying Feng, Heng Lian, Liugen Xue

Comput. Stat. Data Anal., 2016

2015

Variable selection and estimation for partially linear single-index models with longitudinal data.

Gaorong Li, Peng Lai, Heng Lian

Stat. Comput., 2015

Bayesian quantile regression for partially linear additive models.

Yuao Hu, Kaifeng Zhao, Heng Lian

Stat. Comput., 2015

Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models.

Heng Lian, Jie Meng, Kaifeng Zhao

J. Multivar. Anal., 2015

Simultaneous estimation of linear conditional quantiles with penalized splines.

Heng Lian, Jie Meng, Zengyan Fan

J. Multivar. Anal., 2015

Parametric and semiparametric reduced-rank regression with flexible sparsity.

Heng Lian, Sanying Feng, Kaifeng Zhao

J. Multivar. Anal., 2015

Quantile regression for dynamic partially linear varying coefficient time series models.

Heng Lian

J. Multivar. Anal., 2015

Minimax prediction for functional linear regression with functional responses in reproducing kernel Hilbert spaces.

Heng Lian

J. Multivar. Anal., 2015

A Note on Application of Nesterov's Method in Solving Lasso-Type Problems.

Ye Tian, Heng Lian

Commun. Stat. Simul. Comput., 2015

2014

Empirical likelihood inference for general transformation models with right censored data.

Jianbo Li, Zhensheng Huang, Heng Lian

Stat. Comput., 2014

SCAD-penalized regression in additive partially linear proportional hazards models with an ultra-high-dimensional linear part.

Heng Lian, Jianbo Li, Xingyu Tang

J. Multivar. Anal., 2014

Series expansion for functional sufficient dimension reduction.

Heng Lian, Gaorong Li

J. Multivar. Anal., 2014

Semiparametric Bayesian information criterion for model selection in ultra-high dimensional additive models.

Heng Lian

J. Multivar. Anal., 2014

Variational inferences for partially linear additive models with variable selection.

Kaifeng Zhao, Heng Lian

Comput. Stat. Data Anal., 2014

Partially linear structure identification in generalized additive models with NP-dimensionality.

Heng Lian, Pang Du, Yuanzhang Li, Hua Liang

Comput. Stat. Data Anal., 2014

2013

Bayesian quantile regression for single-index models.

Yuao Hu, Robert B. Gramacy, Heng Lian

Stat. Comput., 2013

Empirical likelihood for partially linear proportional hazards models with growing dimensions.

Xingyu Tang, Jianbo Li, Heng Lian

J. Multivar. Anal., 2013

Quadratic inference functions for partially linear single-index models with longitudinal data.

Peng Lai, Gaorong Li, Heng Lian

J. Multivar. Anal., 2013

Sparse-smooth regularized singular value decomposition.

Zhaoping Hong, Heng Lian

J. Multivar. Anal., 2013

A simple and efficient algorithm for fused lasso signal approximator with convex loss function.

Lichun Wang, Yuan You, Heng Lian

Comput. Stat., 2013

Shrinkage variable selection and estimation in proportional hazards models with additive structure and high dimensionality.

Heng Lian, Jianbo Li, Yuao Hu

Comput. Stat. Data Anal., 2013

Automatic variable selection for longitudinal generalized linear models.

Gaorong Li, Heng Lian, Sanying Feng, Lixing Zhu

Comput. Stat. Data Anal., 2013

2012

Gaussian Process Single-Index Models as Emulators for Computer Experiments.

Robert B. Gramacy, Heng Lian

Technometrics, 2012

On feature selection with principal component analysis for one-class SVM.

Heng Lian

Pattern Recognit. Lett., 2012

Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data.

Peng Lai, Qihua Wang, Heng Lian

J. Multivar. Anal., 2012

Time-varying coefficient estimation in differential equation models with noisy time-varying covariates.

Zhaoping Hong, Heng Lian

J. Multivar. Anal., 2012

BOPA: A Bayesian hierarchical model for outlier expression detection.

Zhaoping Hong, Heng Lian

Comput. Stat. Data Anal., 2012

2011

Semi-varying coefficient models with a diverging number of components.

Gaorong Li, Liugen Xue, Heng Lian

J. Multivar. Anal., 2011

2010

Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images.

Aditya Chopra, Heng Lian

Pattern Recognit., 2010

Sparse Bayesian hierarchical modeling of high-dimensional clustering problems.

Heng Lian

J. Multivar. Anal., 2010

2009

Bayesian Nonlinear Principal Component Analysis Using Random Fields.

Heng Lian

IEEE Trans. Pattern Anal. Mach. Intell., 2009

2008

Automated mapping of large-scale chromatin structure in ENCODE.

Heng Lian, William A. Thompson, Robert E. Thurman, John A. Stamatoyannopoulos, William Stafford Noble, Charles E. Lawrence

Bioinform., 2008

2007

On the Consistency of Bayesian Function Approximation Using Step Functions.

Heng Lian

Neural Comput., 2007

2006

Variational Local Structure Estimation for Image Super-Resolution.

Heng Lian

Proceedings of the International Conference on Image Processing, 2006