Jian Huang

According to our database, Jian Huang authored at least 52 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deep Dimension Reduction for Supervised Representation Learning.

Jian Huang, Yuling Jiao, Xu Liao, Jin Liu, Zhou Yu

IEEE Trans. Inf. Theory, May, 2024

Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models.

Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang

SIAM J. Math. Data Sci., 2024

Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks.

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang

J. Mach. Learn. Res., 2024

Gaussian Interpolation Flows.

Yuan Gao, Jian Huang, Yuling Jiao

J. Mach. Learn. Res., 2024

More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization.

Xu Liu, Heng Lian, Jian Huang

J. Mach. Learn. Res., 2024

Adaptive debiased SGD in high-dimensional GLMs with streaming data.

Ruijian Han, Lan Luo, Yuanhang Luo, Yuanyuan Lin, Jian Huang

CoRR, 2024

2023

Conditional Stochastic Interpolation for Generative Learning.

Ding Huang, Jian Huang, Ting Li, Guohao Shen

CoRR, 2023

Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models.

Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang

CoRR, 2023

Wasserstein Generative Regression.

Shanshan Song, Tong Wang, Guohao Shen, Yuanyuan Lin, Jian Huang

CoRR, 2023

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression.

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang

CoRR, 2023

2022

PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties.

Jian Huang, Yuling Jiao, Xiliang Lu, Yueyong Shi, Qinglong Yang, Yuanyuan Yang

Signal Process., 2022

An Error Analysis of Generative Adversarial Networks for Learning Distributions.

Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang

J. Mach. Learn. Res., 2022

GSDAR: a fast Newton algorithm for ℓ ₀ regularized generalized linear models with statistical guarantee.

Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu

Comput. Stat., 2022

<i>ℓ</i>₀-Regularized high-dimensional accelerated failure time model.

Chao Cheng, Xingdong Feng, Jian Huang, Yuling Jiao, Shuang Zhang

Comput. Stat. Data Anal., 2022

Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction.

Wenlu Tang, Guohao Shen, Yuanyuan Lin, Jian Huang

CoRR, 2022

Deep Sufficient Representation Learning via Mutual Information.

Siming Zheng, Yuanyuan Lin, Jian Huang

CoRR, 2022

Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks.

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang

CoRR, 2022

Approximation with CNNs in Sobolev Space: with Applications to Classification.

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang

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

2021

Wasserstein Generative Learning of Conditional Distribution.

Shiao Liu, Xingyu Zhou, Yuling Jiao, Jian Huang

CoRR, 2021

Relative Entropy Gradient Sampler for Unnormalized Distributions.

Xingdong Feng, Yuan Gao, Jian Huang, Yuling Jiao, Xu Liu

CoRR, 2021

Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks.

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang

CoRR, 2021

Non-asymptotic Error Bounds for Bidirectional GANs.

Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Generative Learning via Euler Particle Transport.

Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Jerry Zhijian Yang

Proceedings of the Mathematical and Scientific Machine Learning, 2021

2020

A Semismooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning.

Yueyong Shi, Jian Huang, Yuling Jiao, Qinglong Yang

IEEE Trans. Neural Networks Learn. Syst., 2020

Generative Learning With Euler Particle Transport.

Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Jerry Zhijian Yang

CoRR, 2020

Learning Implicit Generative Models with Theoretical Guarantees.

Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu

CoRR, 2020

A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models.

Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu

CoRR, 2020

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies.

Yi Yang, Xingjie Shi, Yuling Jiao, Jian Huang, Min Chen, Xiang Zhou, Lei Sun, Xinyi Lin, Can Yang, Jin Liu

Bioinform., 2020

2019

High-dimensional integrative analysis with homogeneity and sparsity recovery.

Xinfeng Yang, Xiaodong Yan, Jian Huang

J. Multivar. Anal., 2019

2018

Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares.

Jian Huang, Yuling Jiao, Xiliang Lu, Liping Zhu

SIAM J. Sci. Comput., 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

A Constructive Approach to $L_0$ Penalized Regression.

Jian Huang, Yuling Jiao, Yanyan Liu, Xiliang Lu

J. Mach. Learn. Res., 2018

A Forward and Backward Stagewise algorithm for nonconvex loss functions with adaptive Lasso.

Xingjie Shi, Yuan Huang, Jian Huang, Shuangge Ma

Comput. Stat. Data Anal., 2018

SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties.

Jian Huang, Yuling Jiao, Xiliang Lu, Yueyong Shi, Qinglong Yang

CoRR, 2018

2017

A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression.

Yongxiu Cao, Jian Huang, Yuling Jiao, Yanyan Liu

Commun. Stat. Simul. Comput., 2017

2015

Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors.

Patrick Breheny, Jian Huang

Stat. Comput., 2015

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach.

Xingjie Shi, Qing Zhao, Jian Huang, Yang Xie, Shuangge Ma

Bioinform., 2015

Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA.

Qing Zhao, Xingjie Shi, Yang Xie, Jian Huang, Ben-Chang Shia, Shuangge Ma

Briefings Bioinform., 2015

2014

Majorization minimization by coordinate descent for concave penalized generalized linear models.

Dingfeng Jiang, Jian Huang

Stat. Comput., 2014

Similarity of markers identified from cancer gene expression studies: observations from GEO.

Xingjie Shi, Shihao Shen, Jin Liu, Jian Huang, Yong Zhou, Shuangge Ma

Briefings Bioinform., 2014

2012

Identification of breast cancer prognosis markers via integrative analysis.

Shuangge Ma, Ying Dai, Jian Huang, Yang Xie

Comput. Stat. Data Anal., 2012

Integrative prescreening in analysis of multiple cancer genomic studies.

Rui Song, Jian Huang, Shuangge Ma

BMC Bioinform., 2012

2010

Identification of non-Hodgkin's lymphoma prognosis signatures using the CTGDR method.

Shuangge Ma, Yawei Zhang, Jian Huang, Xuesong Han, Theodore Holford, Qing Lan, Nathaniel Rothman, Peter Boyle, Tongzhang Zheng

Bioinform., 2010

Semiparametric prognosis models in genomic studies.

Shuangge Ma, Jian Huang, Mingyu Shi, Yang Li, Ben-Chang Shia

Briefings Bioinform., 2010

2009

Regularized gene selection in cancer microarray meta-analysis.

Shuangge Ma, Jian Huang

BMC Bioinform., 2009

2008

Penalized feature selection and classification in bioinformatics.

Shuangge Ma, Jian Huang

Briefings Bioinform., 2008

2007

Supervised group Lasso with applications to microarray data analysis.

Shuangge Ma, Xiao Song, Jian Huang

BMC Bioinform., 2007

Additive risk survival model with microarray data.

Shuangge Ma, Jian Huang

BMC Bioinform., 2007

Clustering threshold gradient descent regularization: with applications to microarray studies.

Shuangge Ma, Jian Huang

Bioinform., 2007

2006

Regularized binormal ROC method in disease classificationusing microarray data.

Shuangge Ma, Xiao Song, Jian Huang

BMC Bioinform., 2006

2005

A robust two-way semi-linear model for normalization of cDNA microarray data.

Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzella, Marcelo Bento Soares

BMC Bioinform., 2005

Regularized ROC method for disease classification and biomarker selection with microarray data.

Shuangge Ma, Jian Huang

Bioinform., 2005