Jian Huang

Orcid: 0000-0002-5218-9269

Affiliations:
  • Hong Kong Polytechnic University, Department of Applied Mathematics, Hong Kong
  • University of Iowa, Department of Statistics and Actuarial Science, Iowa City, IA, USA
  • University of Washington, Department of Statistics, USA (PhD 1994)


According to our database1, Jian Huang authored at least 45 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Online presence:

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Bibliography

2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models.
CoRR, 2023

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression.
CoRR, 2023

2022
PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties.
Signal Process., 2022

An Error Analysis of Generative Adversarial Networks for Learning Distributions.
J. Mach. Learn. Res., 2022

GSDAR: a fast Newton algorithm for ℓ <sub>0</sub> regularized generalized linear models with statistical guarantee.
Comput. Stat., 2022

<i>ℓ</i><sub>0</sub>-Regularized high-dimensional accelerated failure time model.
Comput. Stat. Data Anal., 2022

Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction.
CoRR, 2022

Deep Sufficient Representation Learning via Mutual Information.
CoRR, 2022

Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks.
CoRR, 2022

Approximation with CNNs in Sobolev Space: with Applications to Classification.
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.
CoRR, 2021

Relative Entropy Gradient Sampler for Unnormalized Distributions.
CoRR, 2021

Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks.
CoRR, 2021

Non-asymptotic Error Bounds for Bidirectional GANs.
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.
Proceedings of the Mathematical and Scientific Machine Learning, 2021

2020
A Semismooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning.
IEEE Trans. Neural Networks Learn. Syst., 2020

Generative Learning With Euler Particle Transport.
CoRR, 2020

Deep Dimension Reduction for Supervised Representation Learning.
CoRR, 2020

Learning Implicit Generative Models with Theoretical Guarantees.
CoRR, 2020

A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models.
CoRR, 2020

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies.
Bioinform., 2020

2019
High-dimensional integrative analysis with homogeneity and sparsity recovery.
J. Multivar. Anal., 2019

2018
Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares.
SIAM J. Sci. Comput., 2018

On the sign consistency of the Lasso for the high-dimensional Cox model.
J. Multivar. Anal., 2018

A Constructive Approach to $L_0$ Penalized Regression.
J. Mach. Learn. Res., 2018

A Forward and Backward Stagewise algorithm for nonconvex loss functions with adaptive Lasso.
Comput. Stat. Data Anal., 2018

SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties.
CoRR, 2018

2017
A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression.
Commun. Stat. Simul. Comput., 2017

2015
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors.
Stat. Comput., 2015

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach.
Bioinform., 2015

Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA.
Briefings Bioinform., 2015

2014
Majorization minimization by coordinate descent for concave penalized generalized linear models.
Stat. Comput., 2014

Similarity of markers identified from cancer gene expression studies: observations from GEO.
Briefings Bioinform., 2014

2012
Identification of breast cancer prognosis markers via integrative analysis.
Comput. Stat. Data Anal., 2012

Integrative prescreening in analysis of multiple cancer genomic studies.
BMC Bioinform., 2012

2010
Identification of non-Hodgkin's lymphoma prognosis signatures using the CTGDR method.
Bioinform., 2010

Semiparametric prognosis models in genomic studies.
Briefings Bioinform., 2010

2009
Regularized gene selection in cancer microarray meta-analysis.
BMC Bioinform., 2009

2008
Penalized feature selection and classification in bioinformatics.
Briefings Bioinform., 2008

2007
Supervised group Lasso with applications to microarray data analysis.
BMC Bioinform., 2007

Additive risk survival model with microarray data.
BMC Bioinform., 2007

Clustering threshold gradient descent regularization: with applications to microarray studies.
Bioinform., 2007

2006
Regularized binormal ROC method in disease classificationusing microarray data.
BMC Bioinform., 2006

2005
A robust two-way semi-linear model for normalization of cDNA microarray data.
BMC Bioinform., 2005

Regularized ROC method for disease classification and biomarker selection with microarray data.
Bioinform., 2005


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