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2020 – today
- 2024
[j93]Chunyang Zhu, Lei Wang, Weihua Zhao
, Heng Lian:
Image classification based on tensor network DenseNet model. Appl. Intell. 54(8): 6624-6636 (2024)- [j92]Wangli Xu, Kehan Wang, Heng Lian:
Linear convergence of decentralized estimation for statistical estimation using gradient method. Neurocomputing 584: 127584 (2024) - [j91]Xiangyong Tan, Ling Peng, Heng Lian, Xiaohui Liu:
Adaptive Huber trace regression with low-rank matrix parameter via nonconvex regularization. J. Complex. 85: 101871 (2024) - [j90]Xu Liu, Heng Lian, Jian Huang:
More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization. J. Mach. Learn. Res. 25: 161:1-161:27 (2024) - [j89]Wenqi Lu, Zhongyi Zhu, Rui Li, Heng Lian:
Statistical performance of quantile tensor regression with convex regularization. J. Multivar. Anal. 200: 105249 (2024) - [j88]Zihao Song, Xiangjian Xu, Heng Lian, Weihua Zhao:
Robust low tubal rank tensor recovery via L2E criterion. Pattern Recognit. 149: 110241 (2024) - [j87]Yue Wang, Wenqi Lu, Heng Lian:
Distributed statistical estimation in quantile regression over a network. Signal Process. 222: 109512 (2024) - [j86]Wangli Xu, Jiamin Liu, Heng Lian:
Distributed Estimation of Support Vector Machines for Matrix Data. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6643-6653 (2024) - 2023
- [j85]Hanbing Zhu, Yuanyuan Zhang, Yehua Li, Heng Lian:
Semiparametric function-on-function quantile regression model with dynamic single-index interactions. Comput. Stat. Data Anal. 182: 107727 (2023) - [j84]Yaohong Yang, Lei Wang, Jiamin Liu, Rui Li, Heng Lian:
Communication-efficient estimation of quantile matrix regression for massive datasets. Comput. Stat. Data Anal. 187: 107812 (2023) - [j83]Yue Wang, Wenqi Lu, Heng Lian:
Best subset selection for high-dimensional non-smooth models using iterative hard thresholding. Inf. Sci. 625: 36-48 (2023) - [j82]Brittany Green, Heng Lian, Yan Yu, Tianhai Zu:
Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions. J. Multivar. Anal. 196: 105175 (2023) - [j81]Yuzi Liu, Ling Peng, Qing Liu, Heng Lian, Xiaohui Liu:
Functional additive expectile regression in the reproducing kernel Hilbert space. J. Multivar. Anal. 198: 105214 (2023) - [j80]Chunyang Zhu, Weihua Zhao, Heng Lian:
Image recognition and classification with HOG based on nonlinear support tensor machine. Multim. Tools Appl. 82(13): 20119-20138 (2023) - [j79]Jiamin Liu, Wangli Xu, Yue Wang, Heng Lian:
Value iteration for streaming data on a continuous space with gradient method in an RKHS. Neural Networks 166: 437-445 (2023) - [j78]Jiamin Liu, Wangli Xu, Fode Zhang, Heng Lian:
Properties of Standard and Sketched Kernel Fisher Discriminant. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10596-10602 (2023) - [j77]Jiamin Liu, Heng Lian:
On Optimal Learning With Random Features. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9536-9541 (2023) - [j76]Yue Wang, Heng Lian:
On Linear Convergence of ADMM for Decentralized Quantile Regression. IEEE Trans. Signal Process. 71: 3945-3955 (2023) - 2022
- [j75]Yue Wang, Yan Zhou, Rui Li, Heng Lian:
Sparse high-dimensional semi-nonparametric quantile regression in a reproducing kernel Hilbert space. Comput. Stat. Data Anal. 168: 107388 (2022) - [j74]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:
Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes. Genom. Proteom. Bioinform. 20(2): 304-321 (2022) - [j73]Shaogao Lv, Heng Lian:
Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions. J. Mach. Learn. Res. 23: 2:1-2:32 (2022) - [j72]Yingying Zhang, Yan-Yong Zhao, Heng Lian:
Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification. J. Mach. Learn. Res. 23: 156:1-156:24 (2022) - [c3]Heng Lian, John Scovil Atwood, Bojian Hou, Jian Wu, Yi He:
Online Deep Learning from Doubly-Streaming Data. ACM Multimedia 2022: 3185-3194 - [c2]Heng Lian:
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space. NeurIPS 2022 - [i4]Heng Lian, John Scovil Atwood, Bojian Hou, Jian Wu, Yi He:
Online Deep Learning from Doubly-Streaming Data. CoRR abs/2204.11793 (2022) - 2021
- [j71]Yingying Zhang, Heng Lian:
Sketched quantile additive functional regression. Neurocomputing 461: 17-26 (2021) - [j70]Fode Zhang, Rui Li, Heng Lian:
Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection. Inf. Sci. 547: 244-254 (2021) - [j69]Guangren Yang, Xiaohui Liu, Heng Lian:
Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces. J. Complex. 66: 101568 (2021) - [j68]Heng Lian, Jiamin Liu, Zengyan Fan:
Distributed learning for sketched kernel regression. Neural Networks 143: 368-376 (2021) - [j67]Heng Lian:
Learning Rate for Convex Support Tensor Machines. IEEE Trans. Neural Networks Learn. Syst. 32(8): 3755-3760 (2021) - [j66]Yue Wang, Weiping Zhang, Heng Lian:
Distributed Partially Linear Additive Models With a High Dimensional Linear Part. IEEE Trans. Signal Inf. Process. over Networks 7: 611-625 (2021) - 2020
- [j65]Xia Cui, Hongmei Lin, Heng Lian:
Partially functional linear regression in reproducing kernel Hilbert spaces. Comput. Stat. Data Anal. 150: 106978 (2020) - [j64]Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu:
A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Comput. Stat. Data Anal. 152: 107039 (2020) - [j63]Fode Zhang, Xuejun Wang, Rui Li, Heng Lian:
Randomized sketches for sparse additive models. Neurocomputing 385: 80-87 (2020) - [j62]Hanbing Zhu, Rui Li, Riquan Zhang, Heng Lian:
Nonlinear functional canonical correlation analysis via distance covariance. J. Multivar. Anal. 180: 104662 (2020) - [j61]Heng Lian, Fode Zhang, Wenqi Lu:
Randomized sketches for kernel CCA. Neural Networks 127: 29-37 (2020) - [j60]Weihua Zhao, Fode Zhang, Heng Lian:
Debiasing and Distributed Estimation for High-Dimensional Quantile Regression. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2569-2577 (2020)
2010 – 2019
- 2019
- [j59]Xia Cui, Weihua Zhao, Heng Lian, Hua Liang:
Pursuit of dynamic structure in quantile additive models with longitudinal data. Comput. Stat. Data Anal. 130: 42-60 (2019) - [j58]Lili Yue, Gaorong Li, Heng Lian, Xiang Wan:
Regression adjustment for treatment effect with multicollinearity in high dimensions. Comput. Stat. Data Anal. 134: 17-35 (2019) - [j57]Jicai Liu, Peirong Xu, Heng Lian:
Estimation for single-index models via martingale difference divergence. Comput. Stat. Data Anal. 137: 271-284 (2019) - [j56]Hongmei Lin, Xuejun Jiang, Heng Lian, Weiping Zhang:
Reduced rank modeling for functional regression with functional responses. J. Multivar. Anal. 169: 205-217 (2019) - [j55]Hanbing Zhu, Riquan Zhang, Zhou Yu, Heng Lian, Yanghui Liu:
Estimation and testing for partially functional linear errors-in-variables models. J. Multivar. Anal. 170: 296-314 (2019) - [j54]Hongmei Lin, Heng Lian, Hua Liang:
Rank reduction for high-dimensional generalized additive models. J. Multivar. Anal. 173: 672-684 (2019) - 2018
- [j53]Jianbo Li, Heng Lian, Xuejun Jiang, Xinyuan Song:
Estimation and testing for time-varying quantile single-index models with longitudinal data. Comput. Stat. Data Anal. 118: 66-83 (2018) - [j52]Weihua Zhao, Yan Zhou, Heng Lian:
Time-varying quantile single-index model for multivariate responses. Comput. Stat. Data Anal. 127: 32-49 (2018) - [j51]Weihua Zhao, Xuejun Jiang, Heng Lian:
A principal varying-coefficient model for quantile regression: Joint variable selection and dimension reduction. Comput. Stat. Data Anal. 127: 269-280 (2018) - [j50]Zengyan Fan, Heng Lian:
Quantile regression for additive coefficient models in high dimensions. J. Multivar. Anal. 164: 54-64 (2018) - [j49]Shaogao Lv, Mengying You, Huazhen Lin, Heng Lian, Jian Huang:
On the sign consistency of the Lasso for the high-dimensional Cox model. J. Multivar. Anal. 167: 79-96 (2018) - 2017
- [j48]Weihua Zhao, Heng Lian, Xinyuan Song:
Composite quantile regression for correlated data. Comput. Stat. Data Anal. 109: 15-33 (2017) - [j47]Heng Lian, Zengyan Fan:
Divide-and-Conquer for Debiased $l_1$-norm Support Vector Machine in Ultra-high Dimensions. J. Mach. Learn. Res. 18: 182:1-182:26 (2017) - [j46]Weihua Zhao, Heng Lian:
Quantile index coefficient model with variable selection. J. Multivar. Anal. 154: 40-58 (2017) - [j45]Yujie Li, Gaorong Li, Heng Lian, Tiejun Tong:
Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models. J. Multivar. Anal. 155: 133-150 (2017) - [j44]Shu Liu, Jinhong You, Heng Lian:
Estimation and model identification of longitudinal data time-varying nonparametric models. J. Multivar. Anal. 156: 116-136 (2017) - [j43]Yuankun Zhang, Heng Lian, Yan Yu:
Estimation and variable selection for quantile partially linear single-index models. J. Multivar. Anal. 162: 215-234 (2017) - 2016
- [j42]Kaifeng Zhao, Heng Lian:
The Expectation-Maximization approach for Bayesian quantile regression. Comput. Stat. Data Anal. 96: 1-11 (2016) - [j41]Weihua Zhao, Heng Lian, Riquan Zhang, Peng Lai:
Estimation and variable selection for proportional response data with partially linear single-index models. Comput. Stat. Data Anal. 96: 40-56 (2016) - [j40]Qi Li, Heng Lian, Fukang Zhu:
Robust closed-form estimators for the integer-valued GARCH (1, 1) model. Comput. Stat. Data Anal. 101: 209-225 (2016) - [j39]Sanying Feng, Heng Lian, Liugen Xue:
A new nested Cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data. Comput. Stat. Data Anal. 102: 98-109 (2016) - [j38]Sanying Feng, Heng Lian, Fukang Zhu:
Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach. Comput. Stat. Data Anal. 103: 139-150 (2016) - [j37]Heng Lian, Hua Liang:
Separation of linear and index covariates in partially linear single-index models. J. Multivar. Anal. 143: 56-70 (2016) - [j36]Heng Lian, Yongdai Kim:
Nonconvex penalized reduced rank regression and its oracle properties in high dimensions. J. Multivar. Anal. 143: 383-393 (2016) - [j35]Heng Lian, Taeryon Choi, Jie Meng, Seongil Jo:
Posterior convergence for Bayesian functional linear regression. J. Multivar. Anal. 150: 27-41 (2016) - [j34]Zengyan Fan, Heng Lian:
Minimax convergence rates for kernel CCA. J. Multivar. Anal. 150: 183-190 (2016) - [j33]Xingyu Tang, Heng Lian:
Mean and quantile boosting for partially linear additive models. Stat. Comput. 26(5): 997-1008 (2016) - 2015
- [j32]Ye Tian, Heng Lian:
A Note on Application of Nesterov's Method in Solving Lasso-Type Problems. Commun. Stat. Simul. Comput. 44(7): 1673-1682 (2015) - [j31]Heng Lian, Sanying Feng, Kaifeng Zhao:
Parametric and semiparametric reduced-rank regression with flexible sparsity. J. Multivar. Anal. 136: 163-174 (2015) - [j30]Heng Lian:
Minimax prediction for functional linear regression with functional responses in reproducing kernel Hilbert spaces. J. Multivar. Anal. 140: 395-402 (2015) - [j29]Heng Lian, Jie Meng, Zengyan Fan:
Simultaneous estimation of linear conditional quantiles with penalized splines. J. Multivar. Anal. 141: 1-21 (2015) - [j28]Heng Lian:
Quantile regression for dynamic partially linear varying coefficient time series models. J. Multivar. Anal. 141: 49-66 (2015) - [j27]Heng Lian, Jie Meng, Kaifeng Zhao:
Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models. J. Multivar. Anal. 141: 81-103 (2015) - [j26]Gaorong Li, Peng Lai, Heng Lian:
Variable selection and estimation for partially linear single-index models with longitudinal data. Stat. Comput. 25(3): 579-593 (2015) - [j25]Yuao Hu, Kaifeng Zhao, Heng Lian:
Bayesian quantile regression for partially linear additive models. Stat. Comput. 25(3): 651-668 (2015) - 2014
- [j24]Heng Lian, Pang Du, Yuanzhang Li, Hua Liang:
Partially linear structure identification in generalized additive models with NP-dimensionality. Comput. Stat. Data Anal. 80: 197-208 (2014) - [j23]Kaifeng Zhao, Heng Lian:
Variational inferences for partially linear additive models with variable selection. Comput. Stat. Data Anal. 80: 223-239 (2014) - [j22]Heng Lian:
Semiparametric Bayesian information criterion for model selection in ultra-high dimensional additive models. J. Multivar. Anal. 123: 304-310 (2014) - [j21]Heng Lian, Gaorong Li:
Series expansion for functional sufficient dimension reduction. J. Multivar. Anal. 124: 150-165 (2014) - [j20]Heng Lian, Jianbo Li, Xingyu Tang:
SCAD-penalized regression in additive partially linear proportional hazards models with an ultra-high-dimensional linear part. J. Multivar. Anal. 125: 50-64 (2014) - [j19]Jianbo Li, Zhensheng Huang, Heng Lian:
Empirical likelihood inference for general transformation models with right censored data. Stat. Comput. 24(6): 985-995 (2014) - 2013
- [j18]Gaorong Li, Heng Lian, Sanying Feng, Lixing Zhu:
Automatic variable selection for longitudinal generalized linear models. Comput. Stat. Data Anal. 61: 174-186 (2013) - [j17]Heng Lian, Jianbo Li, Yuao Hu:
Shrinkage variable selection and estimation in proportional hazards models with additive structure and high dimensionality. Comput. Stat. Data Anal. 63: 99-112 (2013) - [j16]Lichun Wang, Yuan You, Heng Lian:
A simple and efficient algorithm for fused lasso signal approximator with convex loss function. Comput. Stat. 28(4): 1699-1714 (2013) - [j15]Zhaoping Hong, Heng Lian:
Sparse-smooth regularized singular value decomposition. J. Multivar. Anal. 117: 163-174 (2013) - [j14]Peng Lai, Gaorong Li, Heng Lian:
Quadratic inference functions for partially linear single-index models with longitudinal data. J. Multivar. Anal. 118: 115-127 (2013) - [j13]Xingyu Tang, Jianbo Li, Heng Lian:
Empirical likelihood for partially linear proportional hazards models with growing dimensions. J. Multivar. Anal. 121: 22-32 (2013) - [j12]Yuao Hu, Robert B. Gramacy, Heng Lian:
Bayesian quantile regression for single-index models. Stat. Comput. 23(4): 437-454 (2013) - 2012
- [j11]Zhaoping Hong, Heng Lian:
BOPA: A Bayesian hierarchical model for outlier expression detection. Comput. Stat. Data Anal. 56(12): 4146-4156 (2012) - [j10]Zhaoping Hong, Heng Lian:
Time-varying coefficient estimation in differential equation models with noisy time-varying covariates. J. Multivar. Anal. 103(1): 58-67 (2012) - [j9]Peng Lai, Qihua Wang, Heng Lian:
Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data. J. Multivar. Anal. 105(1): 422-432 (2012) - [j8]Heng Lian:
On feature selection with principal component analysis for one-class SVM. Pattern Recognit. Lett. 33(9): 1027-1031 (2012) - [j7]Robert B. Gramacy, Heng Lian:
Gaussian Process Single-Index Models as Emulators for Computer Experiments. Technometrics 54(1): 30-41 (2012) - 2011
- [j6]Gaorong Li, Liugen Xue, Heng Lian:
Semi-varying coefficient models with a diverging number of components. J. Multivar. Anal. 102(7): 1166-1174 (2011) - 2010
- [j5]Heng Lian:
Sparse Bayesian hierarchical modeling of high-dimensional clustering problems. J. Multivar. Anal. 101(7): 1728-1737 (2010) - [j4]Aditya Chopra, Heng Lian:
Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images. Pattern Recognit. 43(8): 2609-2619 (2010)
2000 – 2009
- 2009
- [j3]Heng Lian:
Bayesian Nonlinear Principal Component Analysis Using Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. 31(4): 749-754 (2009) - [i3]Aditya Chopra, Heng Lian:
Total Variation, Adaptive Total Variation and Nonconvex Smoothly Clipped Absolute Deviation Penalty for Denoising Blocky Images. CoRR abs/0906.0434 (2009) - 2008
- [j2]Heng Lian, William A. Thompson, Robert E. Thurman, John A. Stamatoyannopoulos, William Stafford Noble, Charles E. Lawrence:
Automated mapping of large-scale chromatin structure in ENCODE. Bioinform. 24(17): 1911-1916 (2008) - [i2]Heng Lian:
Bayesian Nonlinear Principal Component Analysis Using Random Fields. CoRR abs/0802.1258 (2008) - 2007
- [j1]Heng Lian:
On the Consistency of Bayesian Function Approximation Using Step Functions. Neural Comput. 19(11): 2871-2880 (2007) - [i1]Heng Lian:
Variational local structure estimation for image super-resolution. CoRR abs/0709.1771 (2007) - 2006
- [c1]Heng Lian:
Variational Local Structure Estimation for Image Super-Resolution. ICIP 2006: 1721-1724
Coauthor Index
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