Jianqing Fan
176 catalog papers. Identity-linked publications and additional name matches are distinguished below.
ORCID: 0000-0003-3250-7677
Frederick L. Moore ’18 Professor of Finance and Professor of Operations Research and Financial Engineering at Princeton University
Publications
- Spectral Ranking Inferences Based on General Multiway Comparisons — Operations Research 2026
- Unearthing Financial Statement Fraud: Insights from News Coverage Analysis — Management Science 2026
- Feature augmentations for high-dimensional learning: Applications to stock market prediction using Chinese news data — The Annals of Applied Statistics 2026 (name-matched, not ORCID-linked)
- Causality pursuit from heterogeneous environments via neural adversarial invariance learning — The Annals of Statistics 2025 (name-matched, not ORCID-linked)
- Ranking Inferences Based on the Top Choice of Multiway Comparisons — Journal of the American Statistical Association 2025
- Robust transfer learning with unreliable source data — The Annals of Statistics 2025
- Communication-Efficient Distributed Estimation and Inference for Cox’s Model — Journal of the American Statistical Association 2025
- Robust Matrix Completion with Heavy-Tailed Noise — Journal of the American Statistical Association 2025
- Isotonic mechanism for exponential family estimation in machine learning peer review — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2025 (name-matched, not ORCID-linked)
- Uncertainty Quantification of MLE for Entity Ranking with Covariates — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
- How do noise tails impact on deep ReLU networks? — The Annals of Statistics 2024
- Inference for heteroskedastic PCA with missing data — The Annals of Statistics 2024
- Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression — Journal of the American Statistical Association 2024
- Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games — Operations Research 2024
- Semi-parametric tensor factor analysis by iteratively projected singular value decomposition — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
- Policy Optimization Using Semiparametric Models for Dynamic Pricing — Journal of the American Statistical Association 2024
- Environment invariant linear least squares — The Annals of Statistics 2024 (name-matched, not ORCID-linked)
- Are Latent Factor Regression and Sparse Regression Adequate? — Journal of the American Statistical Association 2024
- Deep neural networks for nonparametric interaction models with diverging dimension — The Annals of Statistics 2024 (name-matched, not ORCID-linked)
- How Much Can Machines Learn Finance from Chinese Text Data? — Management Science 2024
- Communication-Efficient Accurate Statistical Estimation — Journal of the American Statistical Association 2023
- Robust high-dimensional tuning free multiple testing — The Annals of Statistics 2023
- Bridging factor and sparse models — The Annals of Statistics 2023
- Understanding Implicit Regularization in Over-Parameterized Single Index Model — Journal of the American Statistical Association 2023
- Statistical Inference for High-Dimensional Matrix-Variate Factor Models — Journal of the American Statistical Association 2023
- Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution Under Random Designs — Journal of the American Statistical Association 2023
- An ℓp theory of PCA and spectral clustering — The Annals of Statistics 2022
- SIMPLE: Statistical inference on membership profiles in large networks — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
- Learning Latent Factors From Diversified Projections and Its Applications to Over-Estimated and Weak Factors — Journal of the American Statistical Association 2022
- Testability of high-dimensional linear models with nonsparse structures — The Annals of Statistics 2022
- Rejoinder — Journal of the American Statistical Association 2022
- Asymptotic Theory of Eigenvectors for Random Matrices With Diverging Spikes — Journal of the American Statistical Association 2022
- Canonical thresholding for nonsparse high-dimensional linear regression — The Annals of Statistics 2022
- Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction — Journal of the American Statistical Association 2022
- Estimating Number of Factors by Adjusted Eigenvalues Thresholding — Journal of the American Statistical Association 2022
- Measuring Housing Vitality from Multi-Source Big Data and Machine Learning — Journal of the American Statistical Association 2022
- Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
- Asymmetry helps: Eigenvalue and eigenvector analyses of asymmetrically perturbed low-rank matrices — The Annals of Statistics 2021
- Bridging convex and nonconvex optimization in robust PCA: Noise, outliers and missing data — The Annals of Statistics 2021
- A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery — The Annals of Statistics 2021
- The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases — Journal of the American Statistical Association 2021
- Adaptive Huber Regression — Journal of the American Statistical Association 2020
- Entrywise eigenvector analysis of random matrices with low expected rank — The Annals of Statistics 2020
- Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression” — Journal of the American Statistical Association 2020
- Distributed estimation of principal eigenspaces — The Annals of Statistics 2019
- FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control — Journal of the American Statistical Association 2019
- Spectral method and regularized MLE are both optimal for top-$K$ ranking — The Annals of Statistics 2019 (name-matched, not ORCID-linked)
- Robust Measures of Earnings Surprises — The Journal of Finance 2019
- I-LAMM for sparse learning: Simultaneous control of algorithmic complexity and statistical error — The Annals of Statistics 2018
- Large covariance estimation through elliptical factor models — The Annals of Statistics 2018
- Distributed testing and estimation under sparse high dimensional models — The Annals of Statistics 2018
- A new perspective on robust $M$-estimation: Finite sample theory and applications to dependence-adjusted multiple testing — The Annals of Statistics 2018 (name-matched, not ORCID-linked)
- Error Variance Estimation in Ultrahigh-Dimensional Additive Models — Journal of the American Statistical Association 2018
- Embracing the Blessing of Dimensionality in Factor Models — Journal of the American Statistical Association 2018
- Are discoveries spurious? Distributions of maximum spurious correlations and their applications — The Annals of Statistics 2018
- Robust estimation of high-dimensional covariance and precision matrices — Biometrika 2018
- Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model — Journal of the American Statistical Association 2018
- High dimensional semiparametric latent graphical model for mixed data — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017
- Asymptotics of empirical eigenstructure for high dimensional spiked covariance — The Annals of Statistics 2017
- Estimation of the Continuous and Discontinuous Leverage Effects — Journal of the American Statistical Association 2017
- Estimation of the false discovery proportion with unknown dependence — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017
- Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017
- An $\ell_{\infty}$ Eigenvector Perturbation Bound and Its Application — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
- Peter Hall’s contributions to nonparametric function estimation and modeling — The Annals of Statistics 2016
- Projected principal component analysis in factor models — The Annals of Statistics 2016 (name-matched, not ORCID-linked)
- Conditional Sure Independence Screening — Journal of the American Statistical Association 2016
- Multitask Quantile Regression Under the Transnormal Model — Journal of the American Statistical Association 2016
- Guarding against Spurious Discoveries in High Dimensions — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
- Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification — Journal of the American Statistical Association 2016
- QUADRO: A supervised dimension reduction method via Rayleigh quotient optimization — The Annals of Statistics 2015 (name-matched, not ORCID-linked)
- Sparsifying the Fisher linear discriminant by rotation — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2015
- Power Enhancement in High-Dimensional Cross-Sectional Tests — Econometrica 2015
- Multi-Agent Inference in Social Networks: A Finite Population Learning Approach — Journal of the American Statistical Association 2015
- Homogeneity Pursuit — Journal of the American Statistical Association 2015
- Estimation of functionals of sparse covariance matrices — The Annals of Statistics 2015 (name-matched, not ORCID-linked)
- Strong oracle optimality of folded concave penalized estimation — The Annals of Statistics 2014
- Adaptive robust variable selection — The Annals of Statistics 2014 (name-matched, not ORCID-linked)
- Endogeneity in high dimensions — The Annals of Statistics 2014
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models — Journal of the American Statistical Association 2014
- Covariate assisted screening and estimation — The Annals of Statistics 2014
- Spatially Varying Coefficient Model for Neuroimaging Data With Jump Discontinuities — Journal of the American Statistical Association 2014 (name-matched, not ORCID-linked)
- Distributions of Angles in Random Packing on Spheres — Journal of Machine Learning Research 2013 (name-matched, not ORCID-linked)
- Multiscale adaptive smoothing models for the hemodynamic response function in fMRI — The Annals of Applied Statistics 2013 (name-matched, not ORCID-linked)
- Large covariance estimation by thresholding principal orthogonal complements — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2013
- Vast Portfolio Selection With Gross-Exposure Constraints — Journal of the American Statistical Association 2012
- Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection — Journal of the American Statistical Association 2012
- Rejoinder — Journal of the American Statistical Association 2012
- Variance estimation using refitted cross-validation in ultrahigh dimensional regression — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2012
- A road to classification in high dimensional space: the regularized optimal affine discriminant — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2012
- Estimating False Discovery Proportion Under Arbitrary Covariance Dependence — Journal of the American Statistical Association 2012
- High-dimensional covariance matrix estimation in approximate factor models — The Annals of Statistics 2011
- Regularization for Cox’s proportional hazards model with NP-dimensionality — The Annals of Statistics 2011
- Penalized composite quasi-likelihood for ultrahigh dimensional variable selection — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2011
- Multiple testing via FDRL for large-scale imaging data — The Annals of Statistics 2011
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models — Journal of the American Statistical Association 2011
- High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data — Journal of the American Statistical Association 2010
- Nonparametric tests of the Markov hypothesis in continuous-time models — The Annals of Statistics 2010 (name-matched, not ORCID-linked)
- Sure independence screening in generalized linear models with NP-dimensionality — The Annals of Statistics 2010
- Nonparametric estimation of genewise variance for microarray data — The Annals of Statistics 2010
- Estimation in additive models with highly or nonhighly correlated covariates — The Annals of Statistics 2010 (name-matched, not ORCID-linked)
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