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ORCIDJian Huang 0003
Person information
- affiliation: Hong Kong Polytechnic University, Department of Applied Mathematics, Hong Kong
- affiliation: University of Iowa, Department of Statistics and Actuarial Science, Iowa City, IA, USA
- affiliation (PhD 1994): University of Washington, Department of Statistics, USA
Other persons with the same name
- Jian Huang — disambiguation page
- Jian Huang 0001
![[0000-0002-6267-8824]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-6267-8824")
— Huazhong University of Science and Technology, School of Automation, Wuhan, China (and 1 more) - Jian Huang 0002 — Pennsylvania State University
- Jian Huang 0004 — University of Electronic Science and Technology of China, School of Life Science and Technology / Center for Information in BioMedicine, Chengdu, China
- Jian Huang 0005 — University College Cork, Department of Statistics, Ireland (and 1 more)
- Jian Huang 0006 — University of Illinois at Urbana-Champaign, IL, USA (and 1 more)
- Jian Huang 0007 — University of Tennessee, Knoxville, USA
- Jian Huang 0008 — Kinki University, Higashi-Hiroshima, Japan (and 1 more)
- Jian Huang 0009 — Sun Yat-Sen University, Guangzhou, China (and 1 more)
- Jian Huang 0010 — National University of Defense Technology, College of Intelligence Science and Technology, Changsha, China
- Jian Huang 0011 — Zhejiang Wanli University, Institute of Mathematics, Ningbo, China
- Jian Huang 0012 — Chongqing University, School of Electrical Engineering, Chongqing, China
- Jian Huang 0013 — University of Science and Technology Beijing, School of Automation and Electrical Engineering, Key Laboratory of Knowledge Automation for Industrial Processes, Beijing, China
- Jian Huang 0014 — Chinese Academy of Sciences, Institute of Automation, National Laboratory of Pattern Recognition, Beijing, China
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2020 – today
- 2024
[j34]Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang:
Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. J. Mach. Learn. Res. 25: 88:1-88:75 (2024)- [j33]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) - [j32]Yuan Gao, Jian Huang, Yuling Jiao:
Gaussian Interpolation Flows. J. Mach. Learn. Res. 25: 253:1-253:52 (2024) - [j31]Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang:
Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models. SIAM J. Math. Data Sci. 6(4): 847-868 (2024) - [j30]Jian Huang, Yuling Jiao, Xu Liao, Jin Liu, Zhou Yu:
Deep Dimension Reduction for Supervised Representation Learning. IEEE Trans. Inf. Theory 70(5): 3583-3598 (2024) - [i18]Ruijian Han, Lan Luo, Yuanhang Luo, Yuanyuan Lin, Jian Huang:
Adaptive debiased SGD in high-dimensional GLMs with streaming data. CoRR abs/2405.18284 (2024) - 2023
- [i17]Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang:
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression. CoRR abs/2305.00608 (2023) - [i16]Shanshan Song, Tong Wang, Guohao Shen, Yuanyuan Lin, Jian Huang:
Wasserstein Generative Regression. CoRR abs/2306.15163 (2023) - [i15]Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang:
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models. CoRR abs/2309.00771 (2023) - [i14]Ding Huang, Jian Huang, Ting Li, Guohao Shen:
Conditional Stochastic Interpolation for Generative Learning. CoRR abs/2312.05579 (2023) - 2022
- [j29]Chao Cheng, Xingdong Feng, Jian Huang, Yuling Jiao, Shuang Zhang:
ℓ0-Regularized high-dimensional accelerated failure time model. Comput. Stat. Data Anal. 170: 107430 (2022) - [j28]Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu:
GSDAR: a fast Newton algorithm for ℓ 0 regularized generalized linear models with statistical guarantee. Comput. Stat. 37(1): 507-533 (2022) - [j27]Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang:
An Error Analysis of Generative Adversarial Networks for Learning Distributions. J. Mach. Learn. Res. 23: 116:1-116:43 (2022) - [j26]Jian Huang, Yuling Jiao, Xiliang Lu, Yueyong Shi, Qinglong Yang, Yuanyuan Yang:
PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties. Signal Process. 194: 108432 (2022) - [c3]Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang:
Approximation with CNNs in Sobolev Space: with Applications to Classification. NeurIPS 2022 - [i13]Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang:
Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks. CoRR abs/2207.10442 (2022) - [i12]Siming Zheng, Yuanyuan Lin, Jian Huang:
Deep Sufficient Representation Learning via Mutual Information. CoRR abs/2207.10772 (2022) - [i11]Wenlu Tang, Guohao Shen, Yuanyuan Lin, Jian Huang:
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction. CoRR abs/2210.10161 (2022) - 2021
- [c2]Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Jerry Zhijian Yang:
Deep Generative Learning via Euler Particle Transport. MSML 2021: 336-368 - [c1]Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang:
Non-asymptotic Error Bounds for Bidirectional GANs. NeurIPS 2021: 12328-12339 - [i10]Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang:
Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks. CoRR abs/2105.00292 (2021) - [i9]Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang:
An error analysis of generative adversarial networks for learning distributions. CoRR abs/2105.13010 (2021) - [i8]Xingdong Feng, Yuan Gao, Jian Huang, Yuling Jiao, Xu Liu:
Relative Entropy Gradient Sampler for Unnormalized Distributions. CoRR abs/2110.02787 (2021) - [i7]Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang:
Non-Asymptotic Error Bounds for Bidirectional GANs. CoRR abs/2110.12319 (2021) - [i6]Shiao Liu, Xingyu Zhou, Yuling Jiao, Jian Huang:
Wasserstein Generative Learning of Conditional Distribution. CoRR abs/2112.10039 (2021) - 2020
- [j25]Yi Yang, Xingjie Shi, Yuling Jiao, Jian Huang, Min Chen, Xiang Zhou, Lei Sun, Xinyi Lin, Can Yang, Jin Liu:
CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies. Bioinform. 36(7): 2009-2016 (2020) - [j24]Yueyong Shi, Jian Huang, Yuling Jiao, Qinglong Yang:
A Semismooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning. IEEE Trans. Neural Networks Learn. Syst. 31(8): 2993-3006 (2020) - [i5]Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu:
A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models. CoRR abs/2001.05819 (2020) - [i4]Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu:
Learning Implicit Generative Models with Theoretical Guarantees. CoRR abs/2002.02862 (2020) - [i3]Jian Huang, Yuling Jiao, Xu Liao, Jin Liu, Zhou Yu:
Deep Dimension Reduction for Supervised Representation Learning. CoRR abs/2006.05865 (2020) - [i2]Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Jerry Zhijian Yang:
Generative Learning With Euler Particle Transport. CoRR abs/2012.06094 (2020)
2010 – 2019
- 2019
- [j23]Xinfeng Yang, Xiaodong Yan, Jian Huang:
High-dimensional integrative analysis with homogeneity and sparsity recovery. J. Multivar. Anal. 174 (2019) - 2018
- [j22]Xingjie Shi, Yuan Huang, Jian Huang, Shuangge Ma:
A Forward and Backward Stagewise algorithm for nonconvex loss functions with adaptive Lasso. Comput. Stat. Data Anal. 124: 235-251 (2018) - [j21]Jian Huang, Yuling Jiao, Yanyan Liu, Xiliang Lu:
A Constructive Approach to $L_0$ Penalized Regression. J. Mach. Learn. Res. 19: 10:1-10:37 (2018) - [j20]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) - [j19]Jian Huang, Yuling Jiao, Xiliang Lu, Liping Zhu:
Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares. SIAM J. Sci. Comput. 40(4): A2062-A2086 (2018) - [i1]Jian Huang, Yuling Jiao, Xiliang Lu, Yueyong Shi, Qinglong Yang:
SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties. CoRR abs/1810.03814 (2018) - 2017
- [j18]Yongxiu Cao, Jian Huang, Yuling Jiao, Yanyan Liu:
A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression. Commun. Stat. Simul. Comput. 46(6): 4694-4707 (2017) - 2015
- [j17]Qing Zhao, Xingjie Shi, Yang Xie, Jian Huang, Ben-Chang Shia, Shuangge Ma:
Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA. Briefings Bioinform. 16(2): 291-303 (2015) - [j16]Xingjie Shi, Qing Zhao, Jian Huang, Yang Xie, Shuangge Ma:
Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach. Bioinform. 31(24): 3977-3983 (2015) - [j15]Patrick Breheny, Jian Huang:
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors. Stat. Comput. 25(2): 173-187 (2015) - 2014
- [j14]Xingjie Shi, Shihao Shen, Jin Liu, Jian Huang, Yong Zhou, Shuangge Ma:
Similarity of markers identified from cancer gene expression studies: observations from GEO. Briefings Bioinform. 15(5): 671-684 (2014) - [j13]Dingfeng Jiang, Jian Huang:
Majorization minimization by coordinate descent for concave penalized generalized linear models. Stat. Comput. 24(5): 871-883 (2014) - 2012
- [j12]Rui Song, Jian Huang, Shuangge Ma:
Integrative prescreening in analysis of multiple cancer genomic studies. BMC Bioinform. 13: 168 (2012) - [j11]Shuangge Ma, Ying Dai, Jian Huang, Yang Xie:
Identification of breast cancer prognosis markers via integrative analysis. Comput. Stat. Data Anal. 56(9): 2718-2728 (2012) - 2010
- [j10]Shuangge Ma, Jian Huang, Mingyu Shi, Yang Li, Ben-Chang Shia:
Semiparametric prognosis models in genomic studies. Briefings Bioinform. 11(4): 385-393 (2010) - [j9]Shuangge Ma, Yawei Zhang, Jian Huang, Xuesong Han, Theodore Holford, Qing Lan, Nathaniel Rothman, Peter Boyle, Tongzhang Zheng:
Identification of non-Hodgkin's lymphoma prognosis signatures using the CTGDR method. Bioinform. 26(1): 15-21 (2010)
2000 – 2009
- 2009
- [j8]Shuangge Ma, Jian Huang:
Regularized gene selection in cancer microarray meta-analysis. BMC Bioinform. 10 (2009) - 2008
- [j7]Shuangge Ma, Jian Huang:
Penalized feature selection and classification in bioinformatics. Briefings Bioinform. 9(5): 392-403 (2008) - 2007
- [j6]Shuangge Ma, Jian Huang:
Clustering threshold gradient descent regularization: with applications to microarray studies. Bioinform. 23(4): 466-472 (2007) - [j5]Shuangge Ma, Jian Huang:
Additive risk survival model with microarray data. BMC Bioinform. 8 (2007) - [j4]Shuangge Ma, Xiao Song, Jian Huang:
Supervised group Lasso with applications to microarray data analysis. BMC Bioinform. 8 (2007) - 2006
- [j3]Shuangge Ma, Xiao Song, Jian Huang:
Regularized binormal ROC method in disease classificationusing microarray data. BMC Bioinform. 7: 253 (2006) - 2005
- [j2]Shuangge Ma, Jian Huang:
Regularized ROC method for disease classification and biomarker selection with microarray data. Bioinform. 21(24): 4356-4362 (2005) - [j1]Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzella, Marcelo Bento Soares:
A robust two-way semi-linear model for normalization of cDNA microarray data. BMC Bioinform. 6: 14 (2005)
Coauthor Index
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