Ming Yuan
#149,765
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Researcher ORCID ID = 0000-0002-4415-8606
Ming Yuan's AcademicInfluence.com Rankings
Ming Yuancomputer-science Degrees
Computer Science
#7789
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#8195
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Algorithms
#305
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#309
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Computational Linguistics
#1632
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#1649
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Machine Learning
#3005
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#3042
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Computer Science
Ming Yuan's Degrees
- PhD Computer Science Stanford University
- Masters Computer Science Stanford University
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Why Is Ming Yuan Influential?
(Suggest an Edit or Addition)Ming Yuan'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
- Model selection and estimation in regression with grouped variables (2006) (6922)
- Model selection and estimation in the Gaussian graphical model (2007) (1680)
- Composite quantile regression and the oracle Model Selection Theory (2008) (506)
- High Dimensional Semiparametric Gaussian Copula Graphical Models (2012) (496)
- High Dimensional Inverse Covariance Matrix Estimation via Linear Programming (2010) (398)
- Dimension reduction and coefficient estimation in multivariate linear regression (2007) (298)
- On the non‐negative garrotte estimator (2007) (251)
- A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression (2010) (234)
- On Tensor Completion via Nuclear Norm Minimization (2014) (233)
- Efficient Empirical Bayes Variable Selection and Estimation in Linear Models (2005) (219)
- A direct approach to sparse discriminant analysis in ultra-high dimensions (2012) (210)
- SPARSITY IN MULTIPLE KERNEL LEARNING (2010) (176)
- Learning Networks of Heterogeneous Influence (2012) (158)
- GACV for quantile smoothing splines (2006) (136)
- Minimax and Adaptive Prediction for Functional Linear Regression (2012) (134)
- Adaptive covariance matrix estimation through block thresholding (2012) (126)
- Structured variable selection and estimation (2009) (116)
- Doubly Robust Learning for Estimating Individualized Treatment with Censored Data. (2015) (115)
- Efficient multivariate entropy estimation via $k$-nearest neighbour distances (2016) (101)
- Quantitating the cell: turning images into numbers with ImageJ (2017) (94)
- Optimal estimation of the mean function based on discretely sampled functional data: Phase transition (2011) (91)
- An Efficient Variable Selection Approach for Analyzing Designed Experiments (2007) (86)
- Regularized simultaneous model selection in multiple quantiles regression (2008) (82)
- A Fault Diagnosis Method for Industrial Gas Turbines Using Bayesian Data Analysis (2010) (77)
- Sparse Recovery in Large Ensembles of Kernel Machines On-Line Learning and Bandits (2008) (75)
- On the Nonnegative Garrote Estimator (2005) (71)
- Convex regularization for high-dimensional multiresponse tensor regression (2015) (69)
- Reinforced Multicategory Support Vector Machines (2011) (66)
- On Polynomial Time Methods for Exact Low-Rank Tensor Completion (2017) (63)
- Independent component analysis via nonparametric maximum likelihood estimation (2012) (61)
- Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition (2015) (53)
- Doubly penalized likelihood estimator in heteroscedastic regression (2004) (50)
- Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression (2016) (50)
- Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression (2009) (47)
- Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries (2017) (47)
- Statistical Significance of Clustering Using Soft Thresholding (2013) (47)
- On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning (2015) (41)
- Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models (2011) (40)
- Nonparametric Covariance Function Estimation for Functional and Longitudinal Data (2010) (36)
- Efficient Computation of ℓ1 Regularized Estimates in Gaussian Graphical Models (2008) (35)
- The Nonparanormal SKEPTIC (2012) (34)
- ON THE IDENTIFIABILITY OF ADDITIVE INDEX MODELS (2011) (34)
- Nonnegative Garrote Component Selection in Functional ANOVA models (2007) (32)
- ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching (2019) (30)
- Statistical inferences of linear forms for noisy matrix completion (2019) (28)
- Discussion: "A significance test for the lasso" (2014) (27)
- Large Gaussian Covariance Matrix Estimation With Markov Structures (2009) (25)
- On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives (2019) (24)
- Flexible temporal expression profile modelling using the Gaussian process (2006) (23)
- Convex Regularization for High-Dimensional Tensor Regression (2015) (21)
- On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests (2017) (20)
- Predictive Value of Preoperative Multidetector-Row Computed Tomography for Axillary Lymph Nodes Metastasis in Patients With Breast Cancer (2019) (17)
- State price density estimation via nonparametric mixtures (2009) (17)
- Structure-Leveraged Methods in Breast Cancer Risk Prediction (2016) (17)
- Efficient Portfolio Selection in a Large Market (2016) (17)
- Semiparametric censorship model with covariates (2005) (17)
- Risk Classification With an Adaptive Naive Bayes Kernel Machine Model (2015) (16)
- Distance shrinkage and Euclidean embedding via regularized kernel estimation (2014) (15)
- An Empirical Bayes' Approach to Joint Analysis of Multiple Microarray Gene Expression Studies (2011) (15)
- Dimension reduction and parameter estimation for additive index models (2010) (13)
- Human Memory Search as Initial-Visit Emitting Random Walk (2015) (13)
- Efficient Global Approximation of Generalized Nonlinear ℓ1-Regularized Solution Paths and Its Applications (2009) (12)
- CONVERGENCE RATES OF COMPACTLY SUPPORTED RADIAL BASIS FUNCTION REGULARIZATION (2006) (11)
- Rate-Optimal Detection of Very Short Signal Segments (2014) (11)
- Regularized parameter estimation of high dimensional t distribution (2009) (10)
- Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. (2016) (10)
- Structured variable selection in support vector machines (2007) (10)
- Support vector machines with a reject option (2011) (10)
- Automated and Robust Quantification of Colocalization in Dual-Color Fluorescence Microscopy: A Nonparametric Statistical Approach (2017) (10)
- Factorisable Sparse Tail Event Curves (2015) (9)
- Degrees of freedom in low rank matrix estimation (2016) (9)
- Minimax and Adaptive Estimation of Covariance Operator for Random Variables Observed on a Lattice Graph (2016) (9)
- Spatially Adaptive Colocalization Analysis in Dual-Color Fluorescence Microscopy (2017) (9)
- Deconvolving multidimensional density from partially contaminated observations (2002) (8)
- Breast Cancer Risk Prediction Using Electronic Health Records (2017) (8)
- Radial basis function regularization for linear inverse problems with random noise (2013) (8)
- Automatic Smoothing for Poisson Regression (2005) (7)
- STRUCTURED CORRELATION DETECTION WITH APPLICATION TO COLOCALIZATION ANALYSIS IN DUAL-CHANNEL FLUORESCENCE MICROSCOPIC IMAGING. (2016) (6)
- Perturbation Bounds for Orthogonally Decomposable Tensors and Their Applications in High Dimensional Data Analysis (2020) (6)
- Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age (2018) (6)
- Discriminatory power of common genetic variants in personalized breast cancer diagnosis (2016) (6)
- Quantifying predictive capability of electronic health records for the most harmful breast cancer (2018) (5)
- NORM SUPPORT VECTOR MACHINE (2008) (5)
- A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration (2020) (5)
- Comments on "Personalized dose finding using outcome weighted learning". (2017) (4)
- Discussion: Latent variable graphical model selection via convex optimization (2012) (4)
- FACTORISABLE MULTITASK QUANTILE REGRESSION (2015) (4)
- On Estimating Rank-One Spiked Tensors in the Presence of Heavy Tailed Errors (2021) (4)
- Nonparametric empirical Bayesian framework for fluorescence-lifetime imaging microscopy. (2019) (4)
- Effective Tensor Sketching via Sparsification (2017) (4)
- Regularized principal components of heritability (2014) (3)
- Revisiting colocalization via optimal transport (2021) (3)
- Combined Hypothesis Testing on Graphs With Applications to Gene Set Enrichment Analysis (2016) (3)
- Factorisable Multi-Task Quantile Regression (2016) (3)
- Deconvolving Multivariate Density from Random Field (2003) (2)
- Model Selection and Estimation in Regression with Grouped Variables 4 Ming Yuan and (2004) (1)
- LOCALIZING DIFFERENTIALLY EVOLVING COVARIANCE STRUCTURES VIA SCAN STATISTICS. (2018) (1)
- GACV for quantile smoothing splines MingYuan (2004) (1)
- Nonparametric smoothing and its applications in biomedical imaging (2007) (1)
- Degrees of freedom in low rank matrix estimation (2016) (0)
- Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective (2017) (0)
- Sparsity in high-dimensional learning problems (2010) (0)
- COMMENTS on “ MINIMAX ESTIMATION OF LARGE COVARIANCE MATRICES UNDER l 1-NORM ” (2012) (0)
- Large Dimensional Independent Component Analysis: Statistical Optimality and Computational Tractability (2023) (0)
- Comments on “Grouping strategies and thresholding for high dimension linear models” ☆ (2013) (0)
- On Recovering the Best Rank-r Approximation from Few Entries (2021) (0)
- Comment (2016) (0)
- Sparse Regularization for High Dimensional Additive Models (2010) (0)
- Tensor Sketching: Sparsification and Rank-One Projection (2017) (0)
- Econometrics and Operational Research Efficient Portfolio Selection in a Large Market (2016) (0)
- Statistical Analysis of Time Course Microarray Data (2011) (0)
- Doubly Penalized Likelihood Estimator in Heteroscedastic Regression 1 (0)
- Price Density Estimation via Nonparametric Mixtures (2009) (0)
- Computationally and Efficient Inference for Complex Large-scale Data (2016) (0)
- Discussion of “Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation” (2016) (0)
- ADAPTIVE COVARIANCE MATRIX ESTIMATION THROUGH (2014) (0)
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What Schools Are Affiliated With Ming Yuan?
Ming Yuan is affiliated with the following schools:
