Ji Zhu

发表

Piecewise linear regularized solution paths

S. Rosset, Ji Zhu, Saharon Rosset, 2007, 0708.2197.

Multi-class AdaBoost ∗

Trevor Hastie, Ji Zhu, Hui Zou, 2009 .

Sparsity and smoothness via the fused lasso

R. Tibshirani, K. Knight, S. Rosset, 2005 .

` 1 Regularization in Infinite Dimensional Feature Spaces

Nathan Srebro, S. Rosset, Ji Zhu, 2007 .

The doubly regularized support vector machine

H. Zou, Ji Zhu, Li Wang, 2006 .

The Entire Regularization Path for the Support Vector Machine

Robert Tibshirani, Ji Zhu, Trevor J. Hastie, 2004, J. Mach. Learn. Res..

Classification of gene microarrays by penalized logistic regression.

T. Hastie, Ji Zhu, 2004, Biostatistics.

Variable Selection With the Strong Heredity Constraint and Its Oracle Property

Ji Zhu, Nam-Hee Choi, William Li, 2010 .

Regularized Multivariate Regression for Identifying Master Predictors with Application to Integrative Genomics Study of Breast Cancer.

Ji Zhu, Jie Peng, A. Bergamaschi, 2008, The annals of applied statistics.

Boosting as a Regularized Path to a Maximum Margin Classifier

Ji Zhu, Trevor J. Hastie, Saharon Rosset, 2004, J. Mach. Learn. Res..

Variable selection for the multicategory SVM via adaptive sup-norm regularization

Hao Helen Zhang, Ji Zhu, Yufeng Liu, 2008, 0803.3676.

Corrected proof of the result of ‘A prediction error property of the Lasso estimator and its generalization’ by Huang (2003)

S. Rosset, Ji Zhu, Saharon Rosset, 2004 .

Comment on "Support Vector Machines with Applications"

T. Hastie, Ji Zhu, 2006, math/0612824.

Computing the Solution Path for the Regularized Support Vector Regression

Ji Zhu, Lacey Gunter, Ji Zhu, 2005, NIPS.

A Semi-supervised SVM for Manifold Learning

Jian Huang, Ji Zhu, Chun-hung Li, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Kernel Logistic Regression and the Import Vector Machine

Ji Zhu, Trevor J. Hastie, T. Hastie, 2001, NIPS.

NEW MULTICATEGORY BOOSTING ALGORITHMS BASED ON MULTICATEGORY FISHER-CONSISTENT LOSSES.

H. Zou, T. Hastie, Ji Zhu, 2008, The annals of applied statistics.

Discussion of Boosting Papers

Trevor Hastie, Robert Tibshirani, Ji Zhu, 2003 .

Margin Maximizing Loss Functions

Ji Zhu, Trevor J. Hastie, Saharon Rosset, 2003, NIPS.

Partial Correlation Estimation by Joint Sparse Regression Models

Pei Wang, Jie Peng, Ji Zhu, 2008, Journal of the American Statistical Association.

Hybrid huberized support vector machines for microarray classification

Li Wang, Ji Zhu, Hui Zou, 2007, ICML '07.

A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning

Ji Zhu, Hui Zou, Trevor J. Hastie, 2004, NIPS.

Doubly Regularized REML for Estimation and Selection of Fixed and Random Effects in Linear Mixed-Effects Models

Ji Zhu, Sijian Wang, P. X. Song, 2010 .

Automatic Bias Correction Methods in Semi-supervised Learning

H. Zou, T. Hastie, Ji Zhu, 2019 .

A Note on the Unification of Adaptive Online Learning

Yang Liu, James T. Kwok, Wenwu He, 2017, IEEE Transactions on Neural Networks and Learning Systems.

L1-Norm Quantile Regression

Ji Zhu, Youjuan Li, 2008 .

Quantile Regression in Reproducing Kernel Hilbert Spaces

Ji Zhu, Youjuan Li, Yufeng Liu, 2007 .

Chapter 2 VARIABLE SELECTION FOR THE LINEAR SUPPORT VECTOR MACHINE

H. Zou, Ji Zhu, 2018 .

Measuring the dissimilarity of multiplex networks: An empirical study of international trade networks

Ji Zhu, Wenhua Shi, Xiaohang Zhang, 2017 .

Degrees of Freedom of the Reduced Rank Regression

Ji Zhu, Naisyin Wang, A. Mukherjee, 2012 .

THE DOUBLY REGULARIZED SUPPORT VECTOR MACHINE 591 model (

H. Zou, Ji Zhu, Li Wang, 2006 .

College adjustment in University of Michigan students with Crohn's and colitis

Ji Zhu, Sijian Wang, J. Adler, 2008, Inflammatory bowel diseases.

�-norm Support Vector Machines

R. Tibshirani, T. Hastie, S. Rosset, 2003 .

Comment: Ridge Regression, Ranking Variables and Improved Principal Component Regression

Xuefei Zhang, Ji Zhu, Gongjun Xu, 2020, Technometrics.

Frequentist model averaging estimation for the censored partial linear quantile regression model

Ji Zhu, Xiaoling Lu, Liuquan Sun, 2017 .

VARIABLE SELECTION FOR THE LINEAR SUPPORT VECTOR MACHINE

H. Zou, Ji Zhu, 2020 .

Discussions of boosting papers, and rejoinders

Trevor Hastie, Peter J. Bickel, Robert Tibshirani, 2004 .

Resveratrol has antiinflammatory and antifibrotic effects in the peptidoglycan‐polysaccharide rat model of Crohn's disease

Ji Zhu, G. Christman, J. Adler, 2012, Inflammatory bowel diseases.

Group variable selection via a hierarchical lasso and its oracle property

Ji Zhu, Nengfeng Zhou, 2010, 1006.2871.

Discussion of "Least angle regression" by Efron et al

S. Rosset, Ji Zhu, 2004, math/0406470.

Comment on "Support Vector Machines with Applications"

T. Hastie, Ji Zhu, 2006, math/0612824.

Doubly Penalized Buckley–James Method for Survival Data with High‐Dimensional Covariates

Bin Nan, Sijian Wang, Ji Zhu, 2008, Biometrics.

BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btm364 Data and text mining Analysis of array CGH data for cancer studies using

Ji Zhu, Youjuan Li, Ji Zhu, 2022 .

Variable Selection for Model‐Based High‐Dimensional Clustering and Its Application to Microarray Data

Ji Zhu, Sijian Wang, 2008, Biometrics.

A ug 2 01 0 Group Variable Selection via a Hierarchical Lasso and Its Oracle Property Nengfeng Zhou Consumer Credit Risk Solutions Bank of America Charlotte , NC 28255

Ji Zhu, Nengfeng Zhou, Ji Zhu, 2010 .

l1 Regularization in Infinite Dimensional Feature Spaces

Ji Zhu, Nathan Srebro, Saharon Rosset, 2007, COLT.

An Interrelationship Between Autophagy and Filamentous Growth in Budding Yeast

Ji Zhu, Li Wang, Anuj Kumar, 2007, Genetics.

THE DOUBLY REGULARIZED SUPPORT

H. Zou, Ji Zhu, Li Wang, 2006 .

1-norm Support Vector Machines

Robert Tibshirani, Ji Zhu, Trevor J. Hastie, 2003, NIPS.

�-norm Support Vector Machines

R. Tibshirani, T. Hastie, S. Rosset, 2003 .

REMAS: a new regression model to identify alternative splicing events from exon array data

Minping Qian, Ji Zhu, Hao Zheng, 2009, BMC Bioinformatics.

Efficient Computation and Model Selection for the Support Vector Regression

Ji Zhu, Lacey Gunter, Ji Zhu, 2007, Neural Computation.

Variable selection for multicategory SVM via sup-norm regularization

Ji Zhu, Yichao Wu, Hao Helen Zhang, 2006 .

Financial market forecasting using a two-step kernel learning method for the support vector regression

Li Wang, Ji Zhu, Ji Zhu, 2010, Ann. Oper. Res..

Regularized Semiparametric Estimation for Ordinary Differential Equations

Yun Li, Ji Zhu, Naisyin Wang, 2015, Technometrics.

Improved centroids estimation for the nearest shrunken centroid classifier

Ji Zhu, Sijian Wang, Ji Zhu, 2007, Bioinform..

Reduced rank ridge regression and its kernel extensions

Ji Zhu, Ashin Mukherjee, Ji Zhu, 2011, Stat. Anal. Data Min..

Two-Stage Regularized Linear Discriminant Analysis for 2-D Data

Ji Zhu, Jianhua Zhao, Lei Shi, 2015, IEEE Transactions on Neural Networks and Learning Systems.

A Flexible Latent Space Model for Multilayer Networks

Ji Zhu, Xuefei Zhang, Songkai Xue, 2020, ICML.

Regularized Least Absolute Deviations Regression and an Efficient Algorithm for Parameter Tuning

Michael D. Gordon, Ji Zhu, Li Wang, 2006, Sixth International Conference on Data Mining (ICDM'06).

Hybrid huberized support vector machines for microarray classification and gene selection

Li Wang, Ji Zhu, Hui Zou, 2008, Bioinform..

Variable Selection for Qualitative Interactions in Personalized Medicine While Controlling the Family-Wise Error Rate

Lacey Gunter, Susan Murphy, Ji Zhu, 2011, Journal of biopharmaceutical statistics.

Hierarchically penalized Cox regression with grouped variables

Bin Nan, Sijian Wang, Ji Zhu, 2009 .

Doubly regularized estimation and selection in linear mixed-effects models for high-dimensional longitudinal data.

Ling Zhou, Ji Zhu, Yun Li, 2018, Statistics and its interface.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis

Yan Zhou, Peter X.-K. Song, Pei Wang, 2017, Genetic epidemiology.

Variable Selection for Optimal Decision Making

Ji Zhu, Lacey Gunter, Susan Murphy, 2007, AIME.

Skeleton of weighted social network

Ji Zhu, X. Zhang, Ji Zhu, 2013 .

Pathway Detection Based on Hierarchical LASSO Regression Model

Minping Qian, Ji Zhu, Hao Zheng, 2009, 2009 2nd International Conference on Biomedical Engineering and Informatics.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis

Ji Zhu, P. Song, Pei Wang, 2017, Genetic epidemiology.

1-norm Support Vector Machines

R. Tibshirani, T. Hastie, Ji Zhu, 2003, NIPS.

Network-Assisted Estimation for Large-dimensional Factor Model with Guaranteed Convergence Rate Improvement.

Yong He, Xinsheng Zhang, Ji Zhu, 2020, 2001.10955.

Image denoising via solution paths

Li Wang, Ji Zhu, Ji Zhu, 2010, Ann. Oper. Res..

Boosting and Support Vector Machines as Optimal Separators

Ji Zhu, Trevor J. Hastie, Saharon Rosset, 2003, IS&T/SPIE Electronic Imaging.

Doubly regularized estimation and selection in linear mixed-effects models for high-dimensional longitudinal data.

Ji Zhu, Sijian Wang, Naisyin Wang, 2018, Statistics and its interface.

Variable Selection for the Linear Support Vector Machine

Ji Zhu, Hui Zou, H. Zou, 2007, Trends in Neural Computation.

Sparse, Flexible and Efficient Modeling using L 1 Regularization

Ji Zhu, Saharon Rosset, Ji Zhu, 2006, Feature Extraction.

Hybrid huberized support vector machines for microarray classification and gene selection

H. Zou, Ji Zhu, Li Wang, 2008, Bioinform..