Selected publications
Manuscripts to be published
- Fan, J., Wang, K., Zhong, Y., and Zhu, Z. (2020+).
Robust High dimensional factor models with applications to statistical machine learning.
Statistical Science
- Fan, J., Ma, C., and Zhong, Y. (2020+).
A Selective Overview of Deep Learning
Statistical Science.
- Chen, Y., Cheng, C. and Fan, J. (2020+).
Asymmetry helps: Eigenvalue and eigenvector analyses of asymmetrically perturbed low-rank matrices.
Manuscript.
- Fan, J., Feng, Y. and Xia, L. (2019+).
A conditional dependence measure with applications to undirected graphical models.
Journal of Econometrics,to appear.
- Bradic, J., Fan, J., and Zhu, Y. (2019+).
Testability of high-dimensional linear models with non-sparse structures.
Annals of Statistics, to appear.
- Fan, J., Guo, Y., and Jiang, B. (2019).
Adaptive Huber regression on Markov-dependent data.
Stochastic Processes and Their Applications.
- Abbe, E., Fan, J., Wang, K. and Zhong, Y. (2019+)
Entrywise eigenvector analysis of random matrices with low expected rank.
Annals of Statistics
- Fan, J., Ke, Y., and Liao, Y. (2019+).
Augmented Factor Models with Applications to Validating Market Risk Factors
and Forecasting Bond Risk Premia.
Journal of Econometrics , to appear.
- Wang, S., Fan, J., Pocock, G. Arena, E.T., Eliceiri, K.W. and Yuan, M.
Structured correlation detection with application to colocalization analysis in dual-channel fluorescence microscopic imaging.
Statistica Sinica
Manuscripts under review
- Silin, I. and Fan, J. (2020).
Hypothesis testing for eigenspaces of covariance matrix.
Manuscript.
- Fan, J., Wang, Z., Xie, Y., and Yang, Z. (2020).
A Theoretical Analysis of Deep Q-Learning.
Manuscript.
- Chen, Y., Fan, J., Ma, C., and Yan, Y. (2020).
Bridging convex and nonconvex optimization in robust PCA: noise, outliers, and missing Data.
Manuscript.
- Chen, E.Y., Fan, J., and Li, E. (2020).
Statistical inference for high-dimensional matrix-variate factor model.
Manuscript.
- Fan, J., Fan, Y., Han, X. and Lv, J. (2019).
SIMPLE: statistical inference on membership profiles in large network.
Manuscript.
- Fan, J., Weng, H. and Zhou, Y. (2019).
Optimal estimation of functionals of high-dimensional mean and covariance matrix.
Manuscript.
- Fan, J., Guo, J., and Zheng, S. (2019).
Estimating number of factors by adjusted eigenvalues thresholding.
Manuscript.
- Fan, J. and Liao, Y. (2019).
Learning latent factors from diversified projections and its applications to over-estimated and weak factors.
Manuscript.
- Fan, J., Guo, Y., Wang, K. (2019).
Communication-Efficient Accurate Statistical Estimation.
Manuscript.
- Fan, J., Jiang, B., and Qiang Sun (2019).
Bayesian Factor-adjusted Sparse Regression
Manuscript.
- Chen, Y., Chen, Y., Fan, J., Ma, C., Yan, Y. (2019).
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
Manuscript.
- Fan, J., Fan, Y., Han, X. and Lv, J. (2019).
Asymptotic Theory of Eigenvectors for Large Random Matrices
Manuscript.
- Ke, Z., Bose, K., and Fan, J. (2018).
Higher Moment Estimation for Elliptically-distributed Data: Is it Necessary to Use a Sledgehammer to Crack an Egg?
Manuscript.
- Fan, J., Liu, H., Wang, Z. and Yang, Z. (2018).
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval.
Manuscript.
- Balasubramanian, K., Fan, J., and Yang, Z. (2018).
Tensor methods for additive index models under discordance and heterogeneity.
Manuscript.
- Fan, J. and Zhong, Y. (2018).
Optimal subspace estimation using overidentifying vectors via generalized method of moments.
Manuscript.
- Fan, J., Jiang, B., and Sun, Q. (2018).
Hoeffding's Inequality for Markov Chains and its Applications to Statistical Learning.
Manuscript.
- Fan, J., Wang, W., and Zhu, Z.W. (2016).
A shrinkage principle for heavy-tailed data:
High-dimensional robust low-rank matrix recovery.
Manuscript.
- Fan, J., Imai, K., Liu, H., Ning, Y., Yang, X. (2016).
Improving Covariate Balancing Propensity Score: A Doubly Robust and Efficient Approach.
Manuscript.