Hao Helen Zhang | Academic Influence

Hao Helen Zhang's AcademicInfluence.com Rankings

Hao Helen Zhang

Mathematics

#5417

World Rank

#7624

Historical Rank

Statistics

#732

World Rank

#819

Historical Rank

mathematics Degrees

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Mathematics

Hao Helen Zhang's Degrees

PhD Statistics University of California, Berkeley
Masters Statistics University of California, Berkeley
Bachelors Mathematics Peking University

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Why Is Hao Helen Zhang Influential?

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According to Wikipedia, Hao Helen Zhang is a Chinese statistician. She is a professor at the University of Arizona, in the Department of Mathematics, Statistics Interdisciplinary Program, and Applied Mathematics Interdisciplinary Program there. With Bertrand Clarke and Ernest Fokoué, she is the author of the book Principles and Theory for Data Mining and Machine Learning.

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Hao Helen Zhang's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

ON THE ADAPTIVE ELASTIC-NET WITH A DIVERGING NUMBER OF PARAMETERS. (2009) (696)
Adaptive Lasso for Cox's proportional hazards model (2007) (580)
Component selection and smoothing in multivariate nonparametric regression (2006) (549)
Principles and Theory for Data Mining and Machine Learning (2009) (297)
Sure independence screening for ultrahigh dimensional feature space Discussion (2008) (297)
Gene selection using support vector machines with non-convex penalty (2006) (285)
A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables (2009) (220)
Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models (2011) (153)
Component selection and smoothing in smoothing spline analysis of variance models -- COSSO (2003) (141)
Partially functional linear regression in high dimensions (2016) (139)
Variable selection for optimal treatment decision (2013) (130)
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions (2019) (119)
Surface Estimation, Variable Selection, and the Nonparametric Oracle Property. (2011) (113)
Hard or Soft Classification? Large-Margin Unified Machines (2011) (106)
Variable Selection and Model Building via Likelihood Basis Pursuit (2004) (105)
Interaction Screening for Ultrahigh-Dimensional Data (2014) (103)
Weighted Distance Weighted Discrimination and Its Asymptotic Properties (2010) (96)
Support vector machines with adaptive Lq penalty (2007) (84)
Variable selection for the multicategory SVM via adaptive sup-norm regularization (2008) (83)
Model Selection for High-Dimensional Quadratic Regression via Regularization (2014) (81)
Variable Selection for Semiparametric Mixed Models in Longitudinal Studies (2010) (69)
Structured functional additive regression in reproducing kernel Hilbert spaces (2014) (61)
Variable selection for support vector machines via smoothing spline anova (2006) (60)
Graded regulation of cellular quiescence depth between proliferation and senescence by a lysosomal dimmer switch (2019) (60)
Adaptive Elastic Net for Generalized Methods of Moments (2014) (58)
COMPONENT SELECTION AND SMOOTHING FOR NONPARAMETRIC REGRESSION IN EXPONENTIAL FAMILIES (2006) (54)
Sparse Estimation and Inference for Censored Median Regression. (2010) (50)
Automatic model selection for partially linear models (2009) (49)
Machine Learning Techniques for Optimizing Design of Double T-Shaped Monopole Antenna (2020) (45)
Consistent Group Identification and Variable Selection in Regression With Correlated Predictors (2013) (43)
Variable selection for proportional odds model (2007) (41)
Group IIA secreted phospholipase A2 is associated with the pathobiology leading to COVID-19 mortality. (2021) (40)
Robust Model-Free Multiclass Probability Estimation (2010) (40)
Exit from quiescence displays a memory of cell growth and division (2017) (37)
Principal weighted support vector machines for sufficient dimension reduction in binary classification (2017) (31)
On Estimation of Partially Linear Transformation Models (2010) (29)
Multiclass Proximal Support Vector Machines (2006) (29)
MOMENT-BASED METHOD FOR RANDOM EFFECTS SELECTION IN LINEAR MIXED MODELS. (2012) (28)
Probability‐enhanced sufficient dimension reduction for binary classification (2014) (28)
A Note on High-Dimensional Linear Regression With Interactions (2014) (28)
Variable selection for multicategory SVM via sup-norm regularization (2006) (25)
Time‐Varying Latent Effect Model for Longitudinal Data with Informative Observation Times (2012) (24)
Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification (2013) (23)
On optimal treatment regimes selection for mean survival time (2015) (23)
Variable selection for non‐parametric quantile regression via smoothing spline analysis of variance (2013) (22)
N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes (2017) (21)
Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy. (2017) (20)
Interaction Screening for Ultra-High Dimensional Data. (2014) (19)
FIRST: Combining forward iterative selection and shrinkage in high dimensional sparse linear regression (2009) (19)
On Sparse Estimation for Semiparametric Linear Transformation Models (2010) (17)
Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study (2020) (16)
Sparse and efficient estimation for partial spline models with increasing dimension (2013) (15)
Sparse meta-analysis with high-dimensional data. (2016) (15)
kMEn: Analyzing noisy and bidirectional transcriptional pathway responses in single subjects (2017) (13)
Asymptotic Properties of Distance-Weighted Discrimination (2008) (10)
Discussion of "Sure Independence Screening for Ultra-High Dimensional Feature Space. (2008) (10)
JOINT STRUCTURE SELECTION AND ESTIMATION IN THE TIME-VARYING COEFFICIENT COX MODEL. (2016) (10)
Two-Dimensional Solution Surface for Weighted Support Vector Machines (2014) (10)
Nonparametric model selection in hazard regression (2005) (9)
eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs (2015) (9)
Variable selection for covariate‐adjusted semiparametric inference in randomized clinical trials (2012) (9)
Interaction screening by partial correlation (2018) (8)
Interpretation of 'Omics dynamics in a single subject using local estimates of dispersion between two transcriptomes (2018) (8)
GENERAL ESTIMATING EQUATIONS : MODEL SELECTION AND ESTIMATION WITH DIVERGING NUMBER OF PARAMETERS By (2009) (7)
Effect of Intermittent Versus Continuous Low-Dose Aspirin on Nasal Epithelium Gene Expression in Current Smokers: A Randomized, Double-Blinded Trial (2019) (7)
Multiclass Probability Estimation With Support Vector Machines (2019) (7)
Variable selection for SVM via smoothing spline ANOVA (2005) (6)
A model‐free machine learning method for risk classification and survival probability prediction (2014) (6)
Partially functional linear regression in high dimensions BY DEHAN KONG (2016) (6)
Phase II Trial of Chemopreventive Effects of Levonorgestrel on Ovarian and Fallopian Tube Epithelium in Women at High Risk for Ovarian Cancer: An NRG Oncology Group/GOG Study (2019) (5)
Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study (2022) (5)
A nonparametric survival function estimator via censored kernel quantile regressions (2017) (5)
Variable Selection via Basis Pursuit for Non-Gaussian Data (2001) (5)
Sparse linear regression for optimizing design parameters of double T-shaped monopole antennas (2017) (5)
Splines in Nonparametric Regression (2014) (4)
Model building with likelihood basis pursuit (2004) (4)
Bayesian Inference of Odds Ratios in Misclassified Binary Data with a Validation Substudy (2010) (4)
binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions (2019) (4)
Variability, Information, and Prediction (2009) (3)
Iterative selection using orthogonal regression techniques (2013) (2)
Personalized beyond Precision: Designing Unbiased Gold Standards to Improve Single-Subject Studies of Personal Genome Dynamics from Gene Products (2020) (2)
Support Vector Machine Classification for High Dimensional Microarray Data Analysis, With Applications in Cancer Research (2009) (2)
Supervised Learning: Partition Methods (2009) (2)
Sparse Penalized Forward Selection for Support Vector Classification (2016) (2)
Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity (2022) (2)
Variable selection via penalized likelihood with adaptive penalty (2006) (1)
Variable selection for linear transformation models via penalized marginal likelihood (2006) (1)
Unsupervised Learning: Clustering (2009) (1)
Correction to: binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions (2020) (1)
Nonparametric Trace Regression in High Dimensions via Sign Series Representation (2021) (1)
Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data (2016) (1)
Discussion on “Doubly sparsity kernel learning with automatic variable selection and data extraction” (2018) (1)
binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions (2020) (1)
Oracle P-values and variable screening (2017) (1)
Evaluating IPMN and pancreatic carcinoma utilizing quantitative histopathology (2016) (1)
Bayesian Regularized Quantile Regression Analysis Based on Asymmetric Laplace Distribution (2020) (1)
Learning in High Dimensions (2009) (1)
A lysosomal dimmer switch regulates cellular quiescence depth (2018) (1)
Supplementary Materials for Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models (2011) (0)
Boosting Nystr\"{o}m Method (2023) (0)
binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions (2020) (0)
COSSO-type penalized likelihood method for simultaneous nonparametric regression and model selection in exponential Families (2004) (0)
Machines learn ecological networks: automated discovery of ecological networks based on empirical data (2023) (0)
Exit from quiescence displays a memory of cell growth and division (2017) (0)
Institute of Statistics Mimeo Series No . 2576 Nonparametric Model Selection in Hazard Regression (2005) (0)
Automatic Model Structure Selection (2009) (0)
Splines in Nonparametric RegressionBased in part on the article “Splines in nonparametric regression” by Grace Wahba, which appeared in the Encyclopedia of Environmetrics. (2013) (0)
Nonparametric Methods for Big Data Analytics (2018) (0)
Linear Algorithms for Robust and Scalable Nonparametric Multiclass Probability Estimation (2022) (0)
Bayesian Inference of Odds Ratios inMisclassified Binary Data with a Validation (2010) (0)
Linear Algorithms for Nonparametric Multiclass Probability Estimation (2022) (0)
Some Recent Developments in Parametric and Nonparametric Regression Models (2012) (0)
Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data (2016) (0)
N-W Kernel Regression Estimation for Correlation Function of Bivariate Extremes Copula Function (2018) (0)
Penalized asymptotic likelihood approach for linear transformation model selection (2007) (0)
Sparse and efficient estimation for partial spline models with increasing dimension (2013) (0)
Institute of Statistics Mimeo Series No . 2579 Adaptive-LASSO for Cox ’ s Proportional Hazards Model (2006) (0)
The L q Support Vector Machine (2009) (0)
Model Selection in High‐Dimensional Regression (2022) (0)
Regularized Generalized Linear Models with Interaction Effects [R package RAMP version 2.0.2] (2020) (0)
Linear Regression Models (2020) (0)
Sparse Learning with Non-convex Penalty in Multi-classification (2021) (0)
New Wave Nonparametrics (2009) (0)
Supplementary Material for Partially Functional Linear Regression in High Dimensions (2015) (0)
N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes (2017) (0)
A pan-cancer analysis of thioredoxin-interacting protein as an immunological and prognostic biomarker (2022) (0)

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Other Resources About Hao Helen Zhang

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What Schools Are Affiliated With Hao Helen Zhang?

Hao Helen Zhang is affiliated with the following schools: